The 18kD translocator protein (TSPO) is used as a positron emission tomography (PET) target to quantify neuroinflammation in patients. In Alzheimer’s disease (AD), the cerebellum is the pseudo-reference region for comparison with the cerebral cortex due to the absence of AD pathology and lower levels of TSPO. However, using the cerebellum as a pseudo-reference region is debated, with other brain regions suggested as more suitable. This paper aimed to establish the neuroinflammatory differences between the temporal cortex and cerebellar cortex, including TSPO expression. Using 60 human post-mortem samples encompassing the spectrum of Braak stages (I–VI), immunostaining for pan-Aβ, hyperphosphorylated (p)Tau, TSPO and microglial proteins Iba1, HLA–DR and MSR-A was performed in the temporal cortex and cerebellum. In the cerebellum, Aβ but not pTau, increased over the course of the disease, in contrast to the temporal cortex, where both proteins were significantly increased. TSPO increased in the temporal cortex, more than twofold in the later stages of AD compared to the early stages, but not in the cerebellum. Conversely, Iba1 increased in the cerebellum, but not in the temporal cortex. TSPO was associated with pTau in the temporal cortex, suggesting that TSPO positive microglia may be reacting to pTau itself and/or neurodegeneration at later stages of AD. Furthermore, the neuroinflammatory microenvironment was examined, using MesoScale Discovery assays, and IL15 only was significantly increased in the temporal cortex. Together this data suggests that the cerebellum maintains a more homeostatic environment compared to the temporal cortex, with a consistent TSPO expression, supporting its use as a pseudo-reference region for quantification in TSPO PET scans.
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Abkürzungen
Aβ
Amyloid beta
AD
Alzheimer’s disease
APOE
Apolipoprotein E
Cb
Cerebellum
DAB
3,3′-Diaminobenzidine
GM-CSF
Granulocyte–macrophage colony-stimulating factor
HLA–DR
Human leukocyte antigen–DR isotype
Iba1
Ionized calcium-binding adapter molecule 1
MDC
Macrophage-derived chemokine
MSD
MesoScale Discovery
MSR-A
Macrophage scavenging receptor-A
PBR
Peripheral benzodiazepine receptor
PET
Positron emission tomography
ROI
Region of interest
SNP
Single nucleotide polymorphism
TL
Temporal lobe
TSPO
Translocator protein
Introduction
Neuroinflammation, as defined by the reactivity of microglia, has emerged as a key element of the pathogenesis of Alzheimer’s disease (AD) based on genetic findings [1, 2]. Consequently, the need for new methodologies to assess and follow microglial activation in living patients prompted the development of positron emission tomography (PET) ligands for molecular imaging of neuroinflammation [3, 4]. Indeed, it is unclear to what extent microglia, the main immune cells in the brain, promote or respond to neurodegeneration. There is still not a complete understanding as to how microglia participate in the onset and progression of the disease, with the brain environment revealing inflammatory heterogeneity and a mixture of pro- and anti-inflammatory compounds observed post-mortem in late stages of the disease [5, 6]. The immune reactions are clearly complex in AD, with evidence of temporal changes of microglia [7], emphasizing the importance of brain imaging in living patients [8].
Molecular imaging studies in AD have focused on visualising activated microglia, most commonly measured by elevated expression of translocator protein 18 kDa (TSPO), a five transmembrane domain protein mainly located in the outer membrane of microglial mitochondria [9‐11]. One of the limitations associated with the use of TSPO is its inability to distinguish between the different phenotypes expressed by microglia and potentially lacking specificity [12]. The literature shows divergent and sometimes conflicting results on the PET tracers for TSPO which could be explained by the different binding properties of the various PET tracers but also by methodological issues when quantifying the PET signal, such as high signal to noise ratio and low specificity [13‐15]. A second generation of TSPO radioligands, including [18F]DPA-713, [18F]DPA-714, [11C]PBR28 etc., have been developed with the aim to increase their specificity, compared to the first generation. However, it was observed that their binding capability is affected by a single nucleotide polymorphism (SNP) in the TSPO gene denoted rs6971, an Alanine–Threonine substitution at base 147 which causes low, mixed or high-affinity binding in patients [16]. The SNP became an issue in the interpretation of the findings, leading to the current development of a third generation of TSPO radioligands, such as [18F]GE-180. The cerebellum is often used as a pseudo-reference region to assess the cerebral TSPO PET radiotracer binding without the need for arterial blood sampling [4, 17]. Indeed, there is no true reference region as TSPO is expressed in all brain areas. To be used as a pseudo-reference region for basal binding measurements, the cerebellum requires its TSPO concentration to be low and consistent during the disease progression, to detect small binding increases in other regions. Interestingly, the neuropathological status of the cerebellum, in terms of pathology (Braak), microglia and TSPO expression, during the course of AD is currently unclear.
Anzeige
The aims of our study were to: (i) characterise Aβ and tau pathology in the temporal and cerebellar cortex; (ii) explore the expression of TSPO and other microglial markers through the course of the disease; (iii) compare TSPO expression and AD pathology between both regions, particularly in view of the use of the cerebellum as a reference region for in vivo TSPO PET scans; (iv) assess the inflammatory microenvironment of both regions; and (v) determine if the rs6971 polymorphism affects TSPO immunoexpression.
Materials and methods
Cases
Brain tissue from 60 donors was sourced from the South–West Dementia Brain Bank and matched as closely as possible for age, sex and post-mortem delay between groups (Table 1). Cases were selected based on the Braak stage to allow exploration of the development of the pathology and TSPO expression. Formalin-fixed paraffin embedded tissue from the middle/superior temporal gyrus and cerebellum was obtained for immunohistological analysis and frozen tissue from the same area and same cases were used to assess the inflammatory environment with the Mesoscale Discovery (MSD) multiplex assay.
Table 1
Characteristics of the cases
Cases
Braak stages 0–II
Braak stages III–IV
Braak stages V–VI
Sex
7M:13F
11M:9F
9M:11F
Age at death
(years, mean ± SD)
84.95 ± 8.9
86.20 ± 6.4
80.45 ± 7.6
Braak stage
0 = 4
I = 8
II = 8
III = 10
IV = 10
V = 8
VI = 12
APOE genotype
2/2 = 0
2/3 = 3
2/4 = 0
3/3 = 12
3/4 = 3
4/4 = 0
n/a = 2
2/2 = 0
2/3 = 4
2/4 = 0
3/3 = 8
3/4 = 8
4/4 = 0
2/2 = 0
2/3 = 1
2/4 = 1
3/3 = 10
3/4 = 5
4/4 = 3
Post-mortem
delay (hours, mean ± SD)
54.00 ± 32.00
42.56 ± 19.59
37.00 ± 22.03
Total
20
20
20
M male, F female, SD standard deviation, APOE genotype, n/a not available
Immunohistochemistry
6 μm sections of formalin-fixed paraffin-embedded tissue were used to perform immunohistochemistry to target: pan-Aβ (clone 4G8, Biolegend), phosphorylated tau (pTau, clone AT8, ThermoScientific MN1020) and TSPO (rabbit monoclonal anti-PBR antibody targeting TSPO, Abcam 109497) (Table 2). Microglial antibodies employed were: Iba1 (rabbit polyclonal, Wako labs 019-19741), HLA–DR (clone CR3/43, Dako M0775) and macrophage scavenger receptor (MSR)-A (polyclonal goat, R&D AF2708) (Table 2). Antibodies were visualised using the appropriate biotinylated secondary antibodies and the avidin–biotin-peroxidase complex method (Vectastain Elite, Vector Laboratories) with 3,3′-diaminobenzidine (DAB) as the chromogen and 0.05% hydrogen peroxide as the substrate (Vector Laboratories). The sections were counterstained with haematoxylin, dehydrated and mounted with Pertex (Histolab Products AB). A negative control with no primary antibody was included in all runs.
Microglial scavenging receptor with high affinity for Aβ [7]
Image acquisition and analysis
Scanned images of the staining were obtained with the Olympus VS110 automated slide scanner (Olympus America Inc.) at 20× magnification. For each slide, 30 regions of interest (ROIs) of 500 × 500 µm were extracted in the same anatomical region of grey matter using the CSG add-on function to the Olympus VS-Desktop software [6]. ROIs were analysed with Fiji ImageJ v1.53c software (NIH, USA) [19] using an automated macro. For each antibody, a threshold was selected which included only specific staining and this threshold was then applied to all analyses with that antibody. The area fraction labelled by the antibody in each ROI was obtained by quantifying the presence or absence of the staining in each pixel and expressed as protein load (%). Protein loads were obtained by calculating the mean of the 30 images for each area of each case.
Anzeige
Rs6971 genotyping
Cerebellar samples were genotyped for the SNP rs6971 using the PureLink™ Genomic DNA Extraction Mini Kit (ThermoFisher, K182001) to extract DNA as per manufacturers protocol. Purified genomic DNA concentration was established using the NanoDrop™ ND-1000 Microvolume Spectrometer and diluted to a final concentration of 0.9ng/µl in DNAse free water. The TaqMan® SNP Genotyping assay kit (ThermoFisher, C_2512465_20), which contained forward/reverse primers and fluorescent VIC/FAM probes to correspond to A/G DNA bases, was used along with the 2X TaqMan® Genotyping Master Mix (ThermoFisher, 4371353). The following cycle program was performed on the Applied Biosystems StepOnePlus™ Real-Time PCR system: 95 °C for 10min (HOLD) then 40 cycles of 95 °C × 15secs, 60 °C × 1min.
Inflammatory environment assay
Inflammatory proteins were measured using the V-Plex Mesoscale Discovery (MSD) multi-spot assay platform (MesoScale Diagnostics, Rockville USA). Frozen samples of grey matter were prepared using a lysis solution made of: RIPA buffer (ThermoFisher, 89900), protease inhibitors (Sigma, 04693124001) and phosphatase inhibitors (ThermoFisher, 88667) for manual homogenisation via a Hybaid Ribolyser (Bio-Rad, #3589158). Brain homogenates were used for the V-Plex Chemokine Panel 1 (Eotaxin, Eotaxin-2, TARC, IP10, MIP1α, MIP1β, IL8, MCP1, MDC, and MCP4), Cytokine Panel 1 (GM-CSF, IL1α, IL5, IL7, IL12/IL23p40, IL15, IL16, IL17A, TNFβ, VEGF) and Proinflammatory Panel 1 (IFNγ, IL1β, IL2, IL4, IL6, IL8, IL10, IL12p70, IL13, TNFα). Each plate was read on a Meso Quickplex SQ120 with absolute target protein levels (pg/ml) obtained and normalised to the total protein amount [calculated via BCA assay (ThermoFisher, 23225)].
Statistical analysis
Statistical analysis was carried out using the IBM SPSS v28 statistical software package (SPSS Inc. Chicago IL) and GraphPad Prism v9.2 (GraphPad Software. San Diego CA) for the graphs. For each marker, normality of the distribution was assessed by the Shapiro–Wilk test, and the distribution was observed to be non-parametric for all markers except TSPO in the temporal lobe. Comparisons between the different Braak stage groups were carried out using the non-parametric Kruskal–Wallis test followed by Dunn’s post-hoc test if significant, and the parametric one-way ANOVA test with the Tukey’s post-hoc test for TSPO in the temporal lobe. Comparisons between the temporal lobe and cerebellum were performed using Mann–Whitney U test for all markers. Correlations between the different markers were performed using either the Spearman’s test or the Pearson’s test depending on normality. To account for multiple correlation testing, the two-stage step-up Benjamini, Kreiger and Yekutieli test was used to control for the false discovery rate (FDR) in post-hoc analysis. Of note, correlation analysis was performed between the post-mortem tissue and all immunomarkers to ensure that the post-mortem delay did not influence the staining (Additional file 1: Table S5). Adjusted P values less than 0.05 for intergroup comparisons and 0.01 for correlations were considered significant.
Results
Aβ and tau immunohistochemistry
Aβ and pTau immunostaining was quantified in the temporal and cerebellar cortex to explore the differences in severity of AD pathology within these two brain areas. In the temporal cortex, at Braak stages 0–II, plaques were predominantly diffuse in morphology, with dense-cored plaques appearing at later Braak stages (Fig. 1A, B). Quantification showed a significant progressive increase in Aβ load through the Braak stages (Braak 0–II median 1.48%; Braak III–IV median 5.88%; Braak V–VI median 10.87%, P < 0.0001) (Fig. 1C). At Braak stages 0–II, very little pTau was present and mainly observed in neuronal cell bodies, whereas at Braak stages V–VI extensive pTau spread had occurred with the presence of neuropil threads and dystrophic neurites (Fig. 1D, E). Quantification showed a significant progressive increase in pTau load through the Braak stages (Braak 0–II median 0.04%; Braak III–IV median 0.75%; Braak V–VI median 5.27%, P < 0.0001) (Fig. 1F).
Fig. 1
Illustrations and quantification of the immunostaining of Aβ (4G8) and pTau (AT8) expressed as protein load (%) in the temporal cortex (TL: A–F) and cerebellar cortex (Cb: G–L). Significant increases over the course of the disease are observed for Aβ (P < 0.0001) and pTau (P < 0.0001) in the temporal cortex and for Aβ (P = 0.0008) in the cerebellar cortex. No change was detected for pTau in the cerebellum. Counterstaining: Haematoxylin. Scale bar = 50μm
×
In the cerebellar cortex, Aβ deposition was mainly diffuse in pattern, without dense cores, and primarily distributed in the molecular layer (Fig. 1G, H). There was a significant increase in Aβ load across the Braak stages in the cerebellum (Braak 0–II median 0.11%; Braak III–IV median 0.15%; Braak V–VI median 0.27%, P = 0.0008) (Fig. 1I). pTau was not altered in the cerebellar cortex (P = 0.081) (Fig. 1J–L).
Comparing the regions, both Aβ and pTau loads were significantly lower in the cerebellum than in the temporal cortex when examining all cases (Aβ: Cb median 0.16%; TL median 6.19%; pTau: Cb median 0.02%; TL median 0.71%, P < 0.0001) (Fig. 2).
Fig. 2
Comparisons between temporal lobe (TL) and cerebellum (Cb) for Aβ, pTau, TSPO and other microglial markers. Significant difference in load between TL and Cb for Aβ (P < 0.0001), pTau (P < 0.0001), HLA–DR (P < 0.0001) and MSR-A (P < 0.0001). No difference found for TSPO (P = 0.072) or Iba1 (P = 0.537)
×
TSPO immunohistochemistry
TSPO immunostaining showed an intracellular dot-like pattern, consistent with labelling of mitochondria, localised predominantly to microglia and endothelial cells (Fig. 3). TSPO staining was mostly concentrated around the nuclei with some staining apparent in microglial processes (Fig. 3E, F). Neurons and other glial cells were unlabelled, suggesting that TSPO is restricted to cells of mesodermal origin (i.e., microglia [20] and endothelial cells [21]) and not present in the mitochondria of cells derived from neuroectoderm. In the temporal cortex, the TSPO load was significantly increased at Braak stage V–VI compared to Braak stages 0–II or III–IV (Braak 0–II mean 0.67%; Braak III–IV mean 0.72%; Braak V–VI mean 1.41%, P < 0.0001 and P = 0.0001, respectively) (Fig. 4C). In the cerebellum, TSPO exhibited a consistent pattern of staining particularly at the junction of the molecular and granular grey matter layers in Braak stage VI (Fig. 5B). However, there was no overall difference in TSPO load with Braak stage in this region (Braak 0–II median 0.57%; Braak III–IV median 0.65%; Braak V–VI median 0.64%, P = 0.925) (Fig. 5C).
Fig. 3
Illustrations of Iba1 and TSPO staining. Iba1 identifies: A ramified microglia, B intermediate microglial morphology with shorter processes, C amoeboid microglia, and D microglial cluster. E, F shows TSPO + microglia, with TSPO primarily surrounding the nuclei but staining also seen in some processes. G, H TSPO expression in the endothelial cells/smooth muscle cells of blood vessel walls, in the G longitudinal and H horizontal plane. Counterstaining: Haematoxylin. Scale bars = 50um
Fig. 4
Illustrations and quantification in the temporal lobe (TL) of the immunolabelling expressed as protein load (%) for the microglial markers TSPO (A–C), Iba1 (D–F), HLA–DR (G–I) and MSR-A (J–L). A significant increase with Braak stage was seen for TSPO load (P < 0.0001), while no difference between Braak stages was detected for the other microglial markers. Counterstaining: Haematoxylin. Scale bars = 50μm
Fig. 5
Illustrations and quantification in the cerebellar cortex (Cb) of immunostaining expressed as protein load (%) for the microglial markers TSPO (A–C), Iba1 (D–F), HLA–DR (G–I) and MSR-A (J–L). A significant increase with Braak stage was seen for Iba1 load (P = 0.012). Counterstaining: Haematoxylin. Scale bars = 50μm
×
×
×
Other microglial proteins
In the temporal lobe, Iba1 + and HLA–DR + microglia were predominantly ramified in morphology, whereas MSR-A + microglia appeared more amoeboid (Fig. 4). Clustering of microglia was observed with Iba1 (Fig. 3D), HLA–DR and MSR-A (Fig. 4H, k), mainly in Braak stage V–VI cases and consistent with localisation to Aβ plaques, as previously described [22]. However, unlike TSPO, quantification in the temporal cortex showed no significant change in load with Braak stage for Iba1 (Braak 0–II median 0.8%; Braak III–IV median 1.1%; Braak V–VI median 0.89%, P = 0.688), HLA–DR (Braak 0–II median 0.06%; Braak III–IV median 0.04%; Braak V–VI median 0.05%, P = 0.968) or MSR-A (Braak 0–II median 0.23%; Braak III–IV median 0.26%; Braak V–VI median 0.31%, P = 0.126) (Fig. 4F, I, L). In the cerebellar cortex, Iba1 + and HLA–DR + microglia were more ramified compared to those labelled with MSR-A which had an amoeboid shape (Fig. 5). In contrast to the temporal cortex, cerebellar Iba1 load progressively increased with Braak stage (Braak 0–II median 0.4%; Braak III–IV median 1.07%; Braak V–VI median 1.21%, P = 0.012) (Fig. 5F), whereas TSPO (Braak 0–II median 0.57%; Braak III–IV median 0.65%; Braak V–VI median 0.64%, P = 0.925), HLA–DR (Braak 0–II median 0.9%; Braak III–IV median 0.63%; Braak V–VI median 0.54%, P = 0.1) and MSR-A (Braak 0–II median 0.12%; Braak III–IV median 0.13%; Braak V–VI median 0.1%, P = 0.531) loads were not changed (Fig. 5C, I, L).
Anzeige
Comparison between the temporal and cerebellar cortices did not reveal differences in Iba1 (TL median 0.92%; Cb median 1.04%, P = 0.537) or TSPO (TL median 0.81%; Cb median 0.61%, P = 0.072) loads, irrespective of Braak stage. However, there were significantly less HLA–DR in the temporal lobe than the cerebellum (TL median 0.046%; Cb median 0.7%, P < 0.0001) and vice versa for MSR-A (TL median 0.288%; Cb median 0.113%, P < 0.0001) (Fig. 2).
TSPO Rs6971 genotyping
The genotyping results revealed that 9/54 (16.67%) of cases were homozygous for A/A (low-affinity binding for TSPO PET ligand), 22/54 (40.74%) were heterozygous for A/G (mixed-affinity binding) and 23/54 (42.59%) were homozygous for G/G (high-affinity binding) (Fig. 6A), consistent with other population data [23]. There was no significant differences between genotypes when comparing TSPO protein load in the temporal lobe (A/A median 0.89%; A/G median 0.84%; G/G median 0.66%, P = 0.77) or the cerebellum (A/A median 0.87%; A/G median 0.61%; G/G median 0.53%, P = 0.37) (Fig. 6B, C). This shows that the SNP does not affect the TSPO immunostaining.
Fig. 6
rs6971 genotyping of the cohort with A percentage of cases for each genotype defined as: A/A (low-affinity binder), A/G (mixed-affinity binder) or G/G(high-affinity binder)). B, C comparisons between each genotype and TSPO protein load (%) in the temporal lobe (TL) and cerebellum (Cb), respectively, no significant change detected
×
Correlations
Correlations were performed to assess whether Aβ, pTau, TSPO and other microglial markers were related amongst each other and between the temporal lobe and cerebellum. Across all Braak stages, temporal Aβ was positively correlated with cerebellar Aβ (rs = 0.505, P < 0.001), and temporal pTau with both temporal Aβ (rs = 0.751, P < 0.001) and cerebellar Aβ (rs = 0.516, P < 0.001). Significant positive correlations were also observed for temporal TSPO with temporal pTau (rs = 0.465, P < 0.001) and temporal MSR-A (rs = 0.356, P = 0.005) (Table 3).
Table 3
Correlations of pathological and microglial markers across the temporal (TL) and cerebellar (Cb) cortex (all Braak stages)
Aβ (Cb)
pTau (TL)
pTau( Cb)
TSPO (TL)
TSPO (Cb)
Iba1 (TL)
Iba1 (Cb)
HLA–DR (TL)
HLA–DR (Cb)
MSR-A (TL)
MSR-A (Cb)
Aβ (TL)
rs = 0.505
P < 0.001
rs = 0.751
P < 0.001
rs = 0.287
P = 0.032
rs = 0.268
P = 0.04
rs = 0.176
P = 0.193
rs = 0.019
P = 0.889
rs = 0.295
P = 0.027
rs = 0.042
P = 0.765
rs = − 0.118
P = 0.392
rs = 0.061
P = 0.646
rs = − 0.033
P = 0.812
Aβ (Cb)
rs = 0.516
P < 0.001
rs = 0.177
P = 0.187
rs = 0.296
P = 0.026
rs = 0.272
P = 0.04
rs = 0.133
P = 0.33
rs = 0.219
P = 0.102
rs = 0.065
P = 0.647
rs = − 0.143
P = 0.294
rs = 0.121
P = 0.37
rs = − 0.013
P = 0.927
pTau (TL)
rs = 0.339
P = 0.012
rs = 0.465
P < 0.001
rs = 0.095
P = 0.494
rs = 0.100
P = 0.463
rs = 0.319
P = 0.019
rs = 0.129
P = 0.368
rs = − 0.23
P = 0.098
rs = 0.099
P = 0.465
rs = − 0.184
P = 0.191
pTau (Cb)
rs = 0.081
P = 0.547
rs = 0.141
P = 0.297
rs = 0.079
P = 0.561
rs = − 0.004
P = 0.979
rs = − 0.036
P = 0.802
rs = − 0.084
P = 0.539
rs = 0.104
P = 0.442
rs = 0.214
P = 0.12
TSPO (TL)
rs = 0.220
0 = 0.101
rs = 0.010
P = 941
rs = 0.284
P = 0.033
rs = 0.139
P = 0.316
rs = 0.083
P = 0.544
rs = 0.356
P = 0.005
rs = − 0.071
P = 0.612
TSPO (Cb)
rs = − 0.091
P = 0.507
rs = 0.230
P = 0.085
rs = 0.274
P = 0.05
rs = 0.164
P = 0.228
rs = 0.204
P = 0.129
rs = 0.015
P = 0.913
Iba1 (TL)
rs = 0.256
P = 0.057
rs = 0.082
P = 0.56
rs = − 0.008
P = 0.955
rs = − 0.103
P = 0.436
rs = − 0.279
P = 0.043
Iba1 (Cb)
rs = 0.119
P = 0.402
rs = − 0.011
P = 0.933
rs = 0.077
P = 0.569
rs = − 0.071
P = 0.61
HLA–DR (TL)
rs = 0.548
P < 0.001
rs = 0.244
P = 0.075
rs = − 0.08
P = 0.583
HLA–DR (Cb)
rs = 0.088
P = 0.518
rs = 0.087
P = 0.536
MSR-A (TL)
rs = 0.043
P = 0.759
rs Spearman’s rank correlation, significant P values are in bold
TL temporal lobe; Cb cerebellum
Neuroinflammatory environment
To characterise the neuroinflammatory environment, 30 inflammatory analytes were assessed. Only the cytokine IL15 increased progressively with Braak stage in the temporal cortex (P = 0.0189) (Additional file 1: Table S2). No other significant changes were identified with Braak stage in either the temporal cortex or cerebellum (Additional file 1: Tables S1 and S3).
Anzeige
In terms of the relationships between Aβ, pTau, TSPO, other microglial proteins and the inflammatory molecules in the temporal cortex, there were significant negative correlations between TSPO and GM-CSF (rs = − 0.355, P < 0.01) and between HLA–DR and macrophage-derived cytokine (MDC) (rs = − 0.381, P = 0.007) (Table 4). In the cerebellum, there was a significant positive correlation between Iba1 and IL16 (rs = 0.438, P < 0.001) (Table 5). Directly comparing the protein concentration in both regions, negating Braak stage, most markers were significantly increased in the temporal lobe compared to the cerebellum (Additional file 1: Table S4). However, several of the inflammatory proteins were increased in the cerebellum, including VEGF, IL8HA, IL10 and IL2 (Additional file 1: Table S4).
Table 4
Correlations between pathological/microglial proteins and inflammatory markers across all Braak stages in the temporal lobe
Aβ
pTau
TSPO
Iba1
HLA–DR
MSR-A
GM-CSF
rs = − 0.145
P = 0.312
rs = − 0.230
P = 0.111
rs = − 0.355
P < 0.01
rs = − 0.154
P = 0.280
rs = − 0.088
P = 0.554
rs = − 0.023
P = 0.875
IL1α
rs = 0.098
P = 0.0499
rs = − 0.025
P = 0.863
rs = − 0.136
P = 0.337
rs = − 0.103
P = 0
rs = 0.017
P = 0.910
rs = − 0.065
P = 0.652
IL12/IL23p70
rs = − 0.104
P = 0.472
rs = − 0.192
P = 0.187
rs = − 0.105
P = 0.458
rs = 0.060
P = 0.676
rs = 0.201
P = 0.176
rs = − 0.084
P = 0.560
IL15
rs = 0.123
P = 0.393
rs = 0.268
P = 0.063
rs = 0.310
P = 0.025
rs = − 0.094
P = 0.513
rs = − 0.005
P = 0.971
rs = 0.044
P = 0.757
IL16
rs = 0.039
P = 0.786
rs = 0.060
P = 0.682
rs = 0.155
P = 0.274
rs = 0.267
P = 0.059
rs = 0.202
P = 0.174
rs = − 0.161
P = 0.260
IL17A
rs = 0.016
P = 0.915
rs = 0.206
P = 0.156
rs = 0.134
P = 0.344
rs = − 0.145
P = 0.310
rs = − 0.239
P = 0.106
rs = − 0.154
P = 0.280
IL5
rs = − 0.117
P = 0.417
rs = − 0.053
P = 0.718
rs = − 0.107
P = 0.451
rs = 0.091
P = 0.523
rs = 0.160
P = 0.283
rs = − 0.009
P = 0.947
IL7
rs = − 0.297
P = 0.036
rs = − 0.285
P = 0.047
rs = − 0.013
P = 0.925
rs = − 0.123
P = 0.390
rs = 0.144
P = 0.334
rs = 0.004
P = 0.979
TNFβ
rs = − 0.069
P = 0.632
rs = − 0.175
P = 0.229
rs = 0.042
P = 0.767
rs = − 0.065
P = 0.649
rs = − 0.007
P = 0.962
rs = − 0.021
P = 0.883
VEGF
rs = − 0.310
P = 0.028
rs = − 0.081
P = 0.578
rs = − 0.188
P = 0.182
rs = 0.010
P = 0.945
rs = 0.170
P = 0.254
rs = 0.152
P = 0.286
Eotaxin
rs = 0.005
P = 0.974
rs = 0.207
P = 0.153
rs = 0.019
P = 0.895
rs = 0.063
P = 0.662
rs = − 0.256
P = 0.083
rs = − 0.092
P = 0.520
Eotaxin 3
rs = 0.0003
P = 0.998
rs = 0.110
P = 0.451
rs = − 0.014
P = 0.923
rs = − 0.106
P = 0.461
rs = − 0.209
P = 0.158
rs = 0.001
P = 0.993
IL8 (HA)
rs = − 0.176
P = 0.220
rs = 0.092
P = 0.531
rs = 0.067
P = 0.639
rs = 0.016
P = 0.914
rs = − 0.156
P = 0.296
rs = 0.036
P = 0.800
IP10
rs = 0.051
P = 0.725
rs = 0.192
P = 0.186
rs = 0.149
P = 0.293
rs = 0.251
P = 0.075
rs = 0.018
P = 0.906
rs = 0.059
P = 0.682
MCP1
rs = 0.186
P = 0.196
rs = 0.342
P = 0.016
rs = 0.119
P = 0.400
rs = 0.072
P = 0.614
rs = − 0.054
P = 0.718
rs = − 0.003
P = 0.986
MCP4
rs = − 0.0004
P = 0.998
rs = 0.250
P = 0.083
rs = 0.335
P = 0.015
rs = − 0.084
P = 0.557
rs = − 0.219
P = 0.139
rs = − 0.081
P = 0.574
MDC
rs = 0.011
P = 0.942
rs = 0.250
P = 0.084
rs = 0.152
P = 0.281
rs = − 0.070
P = 0.624
rs = − 0.381
P = 0.007
rs = − 0.003
P = 0.982
MIP1α
rs = 0.002
P = 0.991
rs = 0.250
P = 0.084
rs = 0.054
P = 0.702
rs = 0.060
P = 0.675
rs = − 0.150
P = 0.315
rs = 0.002
P = 0.990
MIP1β
rs = − 0.188
P = 0.192
rs = 0.103
P = 0.479
rs = − 0.010
P = 0.944
rs = 0.021
P = 0.883
rs = − 0.140
P = 0.350
rs = − 0.026
P = 0.854
TARC
rs = − 0.015
P = 0.919
rs = 0.046
P = 0754
rs = − 0.177
P = 0.209
rs = 0.0005
P = 0.970
rs = − 0.075
P = 0.618
rs = 0.008
P = 0.957
IFNγ
rs = − 0.030
P = 0.835
rs = − 0.005
P = 0.971
rs = − 0.123
P = 0.386
rs = 0.032
P = 0.821
rs = 0.019
P = 0.897
rs = 0.141
P = 0.325
IL1β
rs = − 0.121
P = 0.401
rs = 0.039
P = 0.791
rs = − 0.088
P = 0.537
rs = 0.088
P = 0.537
rs = − 0.005
P = 0.974
rs = − 0.025
P = 0.864
IL10
rs = − 0.086
P = 0.550
rs = 0.049
P = 0.741
rs = − 0.168
P = 0.233
rs = − 0.023
P = 0.873
rs = − 0.128
P = 0.391
rs = − 0.058
P = 0.684
IL12p70
rs = − 0.163
P = 0.258
rs = − 0.049
P = 0.739
rs = 0.027
P = 0.850
rs = − 0.236
P = 0.095
rs = − 0.169
P = 0.255
rs = 0.002
P = 0.990
IL13
rs = − 0.169
P = 0.241
rs = − 0.016
P = 0.914
rs = 0.000
P = 0.999
rs = − 0.273
P = 0.053
rs = − 0.255
P = 0.084
rs = 0.155
P = 0.276
IL2
rs = − 0.142
P = 0.324
rs = − 0.095
P = 0.515
rs = − 0.134
P = 0.345
rs = − 0.061
P = 0.669
rs = − 0.122
P = 0.413
rs = 0.126
P = 0.337
IL4
rs = − 0.229
P = 0.110
rs = 0.016
P = 0.912
rs = 0.072
P = 0.614
rs = − 0.125
P = 0.382
rs = − 0.111
P = 0.458
rs = 0.159
P = 0.266
IL6
rs = − 0.008
P = 0.958
rs = 0.033
P = 0.820
rs = 0.063
P = 0.655
rs = 0.032
P = 0.823
rs = − 0.057
P = 0.704
rs = 0.115
P = 0.421
IL8
rs = − 0.121
P = 0.401
rs = 0.008
P = 0.954
rs = − 0.031
P = 0.827
rs = 0.000
P = 0.998
rs = − 0.322
P = 0.027
rs = − 0.025
P = 0.860
TNFα
rs = − 0.273
P = 0.055
rs = − 0.103
P = 0.480
rs = − 0.118
P = 0.406
rs = − 0.054
P = 0.708
rs = − 0.221
P = 0.135
rs = − 0.021
P = 0.883
rs Spearman’s rank correlation, significant P values in bold
Table 5
Correlations between the pathological/microglial proteins and inflammatory markers across all Braak stages in the cerebellum
Aβ
pTau
TSPO
Iba1
HLA–DR
MSR-A
GM-CSF
rs = 0.114
P = 0.556
rs = − 0.163
P = 0.398
rs = − 0.237
P = 0.196
rs = 0.031
P = 0.873
rs = 0.049
P = 0.802
rs = 0.136
P = 0.498
IL1α
rs = 0.060
P = 0.674
rs = 0.014
P = 0.920
rs = − 0.121
P = 0.392
rs = 0.086
P = 0.546
rs = − 0.189
P = 0.179
rs = 0.037
P = 0.800
IL12/IL23p70
rs = 0.006
P = 0.969
rs = − 0.074
P = 0.622
rs = − 0.037
P = 0.807
rs = 0.333
P = 0.022
rs = − 0.194
P = 0.191
rs = − 0.069
P = 0.654
IL15
rs = − 0.005
P = 0.974
rs = 0.184
P = 0.193
rs = 0.241
P = 0.086
rs = 0.151
P = 0.286
rs = − 0.118
P = 0.403
rs = 0.079
P = 0.584
IL16
rs = 0.189
P = 0.179
rs = − 0.001
P = 0.992
rs = 0.121
P = 0.391
rs = 0.438
P < 0.001
rs = 0.034
P = 0.810
rs = − 0.018
P = 0.902
IL17A
rs = − 0.180
P = 0.202
rs = − 0.025
P = 0.863
rs = 0.058
P = 0.682
rs = 0.075
P = 0.599
rs = − 0.239
P = 0.088
rs = − 0.011
P = 0.941
IL5
rs = 0.255
P = 0.094
rs = 0.004
P = 0.982
rs = − 0.364
P = 0.015
rs = 0.053
P = 0.733
rs = − 0.177
P = 0.249
rs = 0.005
P = 0.976
IL7
rs = − 0.223
P = 0.464
rs = 0.083
P = 0.789
rs = 0.586
P = 0.035
rs = 0.270
P = 0.372
rs = 0.193
P = 0.528
rs = − 0.182
P = 0.571
TNFβ
rs = − 0.296
P = 0.049
rs = − 0.199
P = 0.189
rs = − 0.088
P = 0.567
rs = 0.172
P = 0.260
rs = − 0.220
P = 0.146
rs = − 0.059
P = 0.709
VEGF
rs = − 0.063
P = 0.655
rs = − 0.088
P = 0.537
rs = − 0.206
P = 0.142
rs = − 0.070
P = 0.622
rs = − 0.229
P = 0.102
rs = − 0.096
P = 0.507
Eotaxin
rs = − 0.129
P = 0.361
rs = − 0.206
P = 0.142
rs = − 0.226
P = 0.108
rs = 0.177
P = 0.209
rs = − 0.212
P = 0.131
rs = − 0.127
P = 0.379
Eotaxin 3
rs = 0.058
P = 0.681
rs = − 0.097
P = 0.493
rs = − 0.077
P = 0.588
rs = − 0.156
P = 0.269
rs = 0.014
P = 0.922
rs = 0.109
P = 0.449
IL8 (HA)
rs = − 0.089
P = 0.532
rs = 0.060
P = 0.673
rs = − 0.023
P = 0.870
rs = 0.056
P = 0.692
rs = − 0.316
P = 0.023
rs = 0.041
P = 0.775
IP10
rs = − 0.059
P = 0.679
rs = − 0.082
P = 0.563
rs = 0.059
P = 0.680
rs = − 0.036
P = 0.799
rs = − 0.016
P = 0.911
rs = 0.040
P = 0.783
MCP1
rs = − 0.117
P = 0.410
rs = − 0.043
P = 0.760
rs = − 0.090
P = 0.524
rs = 0.058
P = 0.658
rs = − 0.151
P = 0.287
rs = 0.129
P = 0.373
MCP4
rs = − 0.153
P = 0.280
rs = − 0.158
P = 0.264
rs = − 0.166
P = 0.240
rs = 0.148
P = 0.295
rs = − 0.222
P = 0.114
rs = − 0.099
P = 0.495
MDC
rs = − 0.135
P = 0.341
rs = − 0.015
P = 0.916
rs = − 0.083
P = 0.557
rs = 0.143
P = 0.311
rs = − 0.233
P = 0.096
rs = 0.049
P = 0.734
MIP1α
rs = − 0.137
P = 0.332
rs = − 0.144
P = 0.308
rs = − 0.184
P = 0.191
rs = 0.184
P = 0.191
rs = − 0.253
P = 0.070
rs = − 0.124
P = 0.389
MIP1β
rs = − 0.299
P = 0.031
rs = − 0.175
P = 0.215
rs = − 0.193
P = 0.171
rs = 0.119
P = 0.402
rs = − 0.238
P = 0.090
rs = 0.006
P = 0.969
TARC
rs = − 0.303
P = 0.029
rs = − 0.074
P = 0.603
rs = − 0.169
P = 0.231
rs = − 0.008
P = 0.957
rs = − 0.142
P = 0.316
rs = − 0.106
P = 0.463
IFNγ
rs = 0.010
P = 0.946
rs = − 0.227
P = 0.113
rs = 0.164
P = 0.257
rs = 0.336
P = 0.017
rs = − 0.165
P = 0.251
rs = − 0.150
P = 0.310
IL1β
rs = − 0.099
P = 0.485
rs = 0.028
P = 0.843
rs = 0.070
P = 0.620
rs = 0.011
P = 0.940
rs = 0.058
P = 0.681
rs = 0.178
P = 0.216
IL10
rs = 0.014
P = 0.924
rs = − 0.226
P = 0.107
rs = − 0.061
P = 0.667
rs = 0.321
P = 0.020
rs = − 0.238
P = 0.089
rs = 0.026
P = 0.858
IL12p70
rs = − 0.042
P = 0.765
rs = − 0.232
P = 0.098
rs = − 0.111
P = 0.432
rs = 0.287
P = 0.039
rs = − 0.130
P = 0.360
rs = − 0.019
P = 0.895
IL13
rs = − 0.129
P = 0.361
rs = − 0.146
P = 0.301
rs = − 0.311
P = 0.025
rs = − 0.137
P = 0.333
rs = − 0.225
P = 0.108
rs = − 0.010
P = 0.947
IL2
rs = − 0.031
P = 0.829
rs = − 0.242
P = 0.087
rs = − 0.076
P = 0.596
rs = 0.340
P = 0.015
rs = − 0.244
P = 0.084
rs = − 0.050
P = 0.734
IL4
rs = 0.122
P = 0.387
rs = − 0.030
P = 0.834
rs = − 0.006
P = 0.968
rs = 0.192
P = 0.174
rs = − 0.196
P = 0.163
rs = − 0.104
P = 0.473
IL6
rs = − 0.063
P = 0.659
rs = 0.032
P = 0.823
rs = 0.048
P = 0.736
rs = 0.055
P = 0.699
rs = − 0.053
P = 0.711
rs = 0.174
P = 0.228
IL8
rs = 0.006
P = 0.967
rs = 0.029
P = 0.836
rs = − 0.092
P = 0.519
rs = − 0.031
P = 0.829
rs = − 0.098
P = 0.491
rs = 0.159
P = 0.271
TNFα
rs = − 0.143
P = 0.312
rs = − 0.237
P = 0.091
rs = − 0.200
P = 0.154
rs = 0.276
P = 0.047
rs = − 0.163
P = 0.247
rs = − 0.052
P = 0.719
rs Spearman’s rank correlation, significant P values in bold
Discussion
In this study, we have explored the expression of the TSPO protein, a PET target used to image neuroinflammation, in the temporal lobe and cerebellum during the pathological course of AD, using Braak stages as markers of severity of the disease. Using a quantitative and automatic approach, Aβ and pTau deposition were investigated in both regions. Our unbiased assessment of key hallmarks of AD pathology demonstrates a lower pTau severity in the cerebellum, consistent with previous semi-quantitative studies [24, 25]. Indeed, the cerebellar pathological environment has been reported to exhibit a similar composition to that of very early AD in the temporal lobe with very low expression of pTau [26]. A key question is whether the cerebellum is a suitable region to use as pseudo-reference for comparison with the other brain areas in PET analysis. Clinical PET studies in AD have used the cerebellum as pseudo-reference region to quantify cerebral specific binding of the TSPO radiotracer [4, 8, 17]. The underlying assumption is that the cerebellum has lower binding that is not altered in the progression of the pathological condition [4, 17, 27]. Our post-mortem data demonstrate less AD pathology in the cerebellum associated with a lower and consistent TSPO expression over the course of the Braak stages, therefore, supporting the cerebellum as a reference region for TSPO binding.
Comparing the expression of microglial proteins showed disparity between the temporal lobe and cerebellum. Overall, the temporal lobe has higher expression of MSR-A, while the cerebellum has higher expression of HLA–DR. However, only Iba1 expression was significantly changed over the course of the disease with an increase in the cerebellum. Interestingly, TSPO was increased in the temporal lobe, with the highest expression between Braak stages III–IV and stages V–VI, but not in the cerebellum. This finding indicates that TSPO could represent late stage activation, potentially demonstrating a more reactive, phagocytic microglia [28], and that although microglia may be spatially redistributed in AD, the quantitative changes within the microglia may relate to their TSPO-labelled mitochondria. Of note, TSPO expression, as detected by the antibody, was observed in microglia and endothelial cells only. With microglia representing 10% [29, 30] and endothelial cells 0.3% [31] of the cerebral cells, our assessment of the staining mainly reflected the TSPO + microglia.
A link was also detected between pTau and TSPO in the temporal lobe, consistent with an imaging study showing associations between [11C]PBR28 (TSPO) and [18F]AV1451 (tau) PET ligands in MCI and AD patients, which was stronger in AD [32]. Furthermore, an examination of clinical progression of AD found that TSPO and tau PET together were the best predictors of disease progression and cognitive decline [33]. The relationship between TSPO and pTau was also reported in a preclinical study with the knockout of TSPO in a mouse model of AD associated with reduced amount of tau aggregates [34]. This implies a longitudinal relationship between tau and TSPO with the pathological protein associated with increased TSPO levels. TSPO expression as a microglial mitochondrial receptor could be a key feature of AD [35] as supported in the preclinical AD model 5XFAD mice, in which Aβ and pTau exposure induced metabolic dysfunction in microglia [36]. Hence, the increased TSPO in the temporal lobe in the late stage of the disease might reflect microglial dysfunction at the level of mitochondria in AD.
Anzeige
Of note, Iba1, a marker of microglial motility [18], was increased in the cerebellum, rather than in the temporal lobe. This indicates microglia sensing changes in the brain homeostasis, potentially linked to Aβ deposition (diffuse plaques), while in late stage (as observed in temporal lobe), microglia cluster around Aβ plaques as reported by us and others [5‐7, 37]. MSR-A expression was not modified in either region over the course of the disease, but its expression was higher in the temporal cortex (i.e., in the region with the more severe pathology) consistent with this marker having a vulnerability to neurodegeneration [7].
The rs6971 polymorphism impacts the binding ability of TSPO radioligands, thus to observe whether the immunostaining of TSPO was dependent on the polymorphism, we genotyped the cases for the SNP. In our cohort, the TSPO genotype corresponding to high-affinity binders had the highest prevalence (42.59%), followed by the mixed-affinity binders (40.74%) and with the low-affinity binders the least prevalent (16.67%), as reported for European populations [23]. Also, the TSPO immunostaining was not affected by the TSPO polymorphism. This could be explained by the difference in the binding site on the TSPO protein, with the radioligand recognising nine amino acid residues across all five transmembrane domains [10], whereas the antibody binding is between amino acid bases 76 and 169.
The inflammatory microenvironment revealed an increase in IL15 in the temporal lobe over the course of the disease. IL15 is secreted by phagocytic cells to induce an immune response primarily from T cells and natural killer (NK) cells. Elevated IL15 levels in the CSF and serum of AD patients correlated with severity of cognitive dysfunction [38, 39], and with its expression associated with age of onset [38]. No differences were observed in the neuroinflammatory environment of the cerebellum, possibly as the result of a more homeostatic brain condition with lower AD pathology and microglial reactivity. The inflammatory status of the human brain presents a conflicting profile, with some studies reporting more inflammatory changes during aging than in AD [40]. However, our study confirms the importance of IL15 in AD, mainly in presence of severe pathology.
Two negative associations were found in the temporal lobe between the granulocyte–macrophage colony-stimulating factor (GM-CSF) with TSPO and the macrophage-derived chemokine (MDC/CCL22) with HLA–DR. GM-CSF is known to stimulate microglial growth and to be associated with reducing proinflammatory cells [41], with increased GM-CSF reported in the CSF of AD patients [42]. This inflammatory protein is currently being examined as a potential therapeutic target due to its ability to stimulate the innate immune system to clear the pathological proteins via microglial phagocytosis [41]. Of note, the negative GM-CSF association with TSPO and the TSPO relation to pTau is consistent with the hypothesis that microglial reactivity participates in pTau spreading [28], possibly due to dysfunctional microglial phagocytic activity as the result of mitochondrial damage in pathologically affected regions [43].
MDC/CCL22 acts on dendritic, natural killer (NK) and T cells to elicit an immune response [44]. T cell infiltration in in the human brain is a recognised feature of AD [5, 45]. HLA–DR, expressed by microglia/perivascular macrophages, is known to interact with T helper cells to initiate the production of antibodies. Interestingly in the temporal lobe, the negative association between MDC/CCL22 and HLA–DR, both required to activate T cells, implies an impaired control of T cell activation.
In the cerebellum, only one positive association was observed between IL16, a CD4 + cell chemoattractant (T cells, monocytes/macrophages), and Iba1. High levels of IL16 have been detected in blood plasma in early stages of AD but not in the later stages [46], consistent with our finding that the cerebellum exhibits early AD pathology. Interestingly, while overall all inflammatory markers were higher in the temporal lobe, four markers were more highly expressed in the cerebellum, namely, VEGF, IL8HA, IL10 and IL2 which may reflect the difference in the regional vulnerability for AD pathology.
Conclusion
Our study supports the cerebellum as an appropriate region to be used as pseudo-reference for the TSPO PET studies, independently of the ligand binding. We also report that TSPO microglial expression appears to be associated with pTau and late stage of the disease, potentially highlighting a microglial profile associated with mitochondrial dysfunction which worsens with disease progression.
Acknowledgements
We would like to thank Dr Laura Palmer at the South West Dementia Brain Bank (SWDBB), their donors and donor’s families for providing brain tissue for this study. Tissue for this study was provided with support from the BDR programme, jointly funded by Alzheimer's Research UK and Alzheimer's Society. The SWDBB is further supported by BRACE (Bristol Research into Alzheimer’s and Care of the Elderly). We would also like to acknowledge the support of the staff of the Histochemical Research Unit, for their help in performing the staining and validating antibodies, for the Biomedical Imaging unit, David Johnston, Regan Doherty, and David Chatelet for their support in the image acquisition and analysis, and to Iain Hartnell for his help with preparing the MSD assay.
Declarations
Ethics approval and consent to participate
The study was carried out in accordance with relevant guidelines and regulations under the South–West Dementia Brain Bank ethical approval (NRES Committee South–West Central Bristol, REC reference: 08/H0106/28 + 5).
Competing interests
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be constructed as a potential competing of interests.
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Konsumieren Menschen täglich 7 Gramm Olivenöl, ist ihr Risiko, an einer Demenz zu sterben, um mehr als ein Vierten reduziert – und dies weitgehend unabhängig von ihrer sonstigen Ernährung. Dafür sprechen Auswertungen zweier großer US-Studien.
In einer Leseranfrage in der Zeitschrift Journal of the American Academy of Dermatology möchte ein anonymer Dermatologe bzw. eine anonyme Dermatologin wissen, ob er oder sie einen Patienten behandeln muss, der eine rassistische Tätowierung trägt.
Der belastende Arbeitsalltag wirkt sich negativ auf die psychische Gesundheit der Angehörigen ärztlicher Berufsgruppen aus. Chirurginnen und Chirurgen bilden da keine Ausnahme, im Gegenteil.
Extreme Arbeitsverdichtung und kaum Supervision: Dr. Andrea Martini, Sprecherin des Bündnisses Junge Ärztinnen und Ärzte (BJÄ) über den Frust des ärztlichen Nachwuchses und die Vorteile des Rucksack-Modells.
