Demographic data and cognitive scores

Prior to the investigation of pathological markers, biographical data and post-mortem interval were investigated for potentially confounding factors with regards to pathological measures. Independent of analytical classification no significant difference in age, PMI or frontal cortical pH was determined between groups (Table 1). With the exception of Braak stage 0 (100 % male) and Braak stage 5 (83.3 % male), the cohort was reasonably balanced for gender. Scores of cognition as established by the MMSE (Fig. 1a, r = −0.67, p < 0.0001, n = 42), CDR global (Fig. 1b, r = 0.69, p < 0.0001, n = 43), CDR memory (Fig. 1b, r = 0.69, p < 0.01, n = 43) and CDR sum of box scores (data not shown, r = 0.55, p < 0.001, n = 33) closely followed Braak stage progression, but not age (data not shown).

Fig. 1 Cognitive performance during disease progression. Assessment scores from ‘Mini Mental State Exam’ (MMSE, a) as well as global and memory scores from the ‘Clinical Dementia Rating’ (CDR, b) are correlated with disease progression based on Braak stage. Significances (p) and Spearman’s correlation index (r) are provided within each graph. Data are expressed as mean ± SEM, ****p < 0.0001 Full size image

Quantification of tau pathology

Initially, phospho-tau pathology was investigated via immunoblots of soluble lysate, established to selectively extract non-fibrillar protein species (see Supplementary Figure 1). The phospho-specific antibody AT8 recognises tau phosphorylated at serine 199, serine 202 and threonine205 residues (p-ser199/ser202/thr205) [9, 27] and is commonly employed by pathologist for post-mortem confirmation of AD diagnosis and for the staging of tau pathology according to Braak stage. Under dot blot conditions, which negate alterations in the electrophoretic mobility of tau between samples, due to different degrees of protein phosphorylation [17] and allows for quantification of total tau species phosphorylated at each investigated epitope, AT8 immunoreactivity was strongly enhanced in AD diagnosed cases, reporting a ~14-fold increase compared to non-AD samples (Fig. 2a i + ii, p < 0.001). A graded increase in AT8 phospho-tau was also observed across grouped Braak stages (Fig. 2aii, low: Br 0–2, intermediate: Br 3–4, high: Br 5–6, p < 0.0001). Post hoc analysis demonstrated significant elevations between low and intermediate (p < 0.01) and low and high classifications (p < 0.0001), yet not between intermediate and high (p > 0.05). In accordance with the use of AT8 for the histopathological classification of tau pathology, dot blot quantification of soluble AT8 phospho-tau demonstrated a strong correlation with Braak staging (Fig. 2aiii, r = 0.81, p < 0.0001), initial elevations of AT8 phosphorylation being reported as significant from Braak 0 at Braak 4 (p < 0.05), which is in line with Braak stage progression for Brodmann area 21, reportedly affected at Braak stage 4 [2].

Fig. 2 Phospho-tau pathology. Dot blots for a AT8, b PHF-1, c CP13 phospho-tau immunoreactivity. Cases within example dot blots are labelled for diagnosis [non-AD control cases (‘C’) and AD] and Braak stage (Br). Analyses stratified for ii) diagnosis, iii) severity (Low: Br 0–2, Intermediate (Inter): Br 3–4 and High: Br 5–6), and (iv) correlation with individual Braak stages are shown. Statistical outcomes are depicted as **p < 0.01, ***p < 0.001, ****p < 0.0001 and Spearman’s correlation (r). The earliest Braak stage at which immunoreactivity was significantly elevated from Braak 0 is also indicated ($) Full size image

Tau phosphorylation was further investigated using two other commonly employed phospho-tau antibodies, PHF-1 (Fig. 2b, p-ser396/ser404) and CP13 (Fig. 2c, p-ser202). As for AT8, PHF-1 and CP13 reactivity was increased in AD compared to non-AD cases (Fig. 2bii + cii, 9- and 13-fold increase for PHF-1 and CP13, respectively, p < 0.0001 for both). Both PHF-1 and CP13 levels also increased with pathology severity (Fig. 2biii + ciii, p < 0.0001), reporting elevations within intermediate and high Braak stages compared to low pathology cases. Also, strong correlations with individual Braak stages were observed with PHF-1 and CP13 (Fig. 2biv + civ, r = 0.80, p < 0.0001 for PHF-1 and r = 0.77, p < 0.0001 for CP13). For the three phospho-epitopes, CP13 changes were detected earliest (Br 0 cf. Br 2: p < 0.05) and PHF-1 latest (Br 0 cf. Br 5, p < 0.05). Phospho-tau dot blots were validated for specificity by means of correlation of immunoreactivity with traditional Western blots in a subset of cases for PHF-1 (r = 0.79, p < 0.0001, n = 18, data not shown). A significant effect of Braak stage (F (5,80) = 10.47, p < 0.0001) and epitope (F (2,80) = 8.61, p < 0.001) and an interaction (F (10,40) = 2.43, p < 0.05) was reported when comparing the phospho-epitope specific antibodies, likely due to the variable magnitude of hyperphosphorylation and differential antibody affinities apparent between Braak stages 2–4. Nevertheless, further analysis demonstrated a robust effect of subject matching, indicating those cases with high AT8 staining also demonstrated high levels of CP13 and PHF-1 staining. This is perhaps unsurprising given the similarity of dot blot immunostaining between epitopes (see example blots in Fig. 2).

Conformational and oligomeric tau

Although hyperphosphorylation is the most extensively studied aspect of tau pathology, several additional protein modifications offer further key parameters in disease pathology. Conformational changes in the natively unfolded structure of the tau protein, leading to an interaction of the N-terminal domain with the microtubule binding domain (MTBD), may be closely modulated by phosphorylation status [81].

Alz-50 was the first antibody derived from paired helical filaments to recognise such a conformational change [37]. Here, its immunoreactivity was unaltered between Non-AD and AD cases (‘diagnosis’) and did not increase when considered across grouped Braak stages (Fig. 3ai–iii, p < 0.05). Despite a failure to detect differences between diagnosis and severity groups, a modest correlation between Alz-50 and Braak stage was observed (Fig. 3aiv, r = 0.32, p < 0.05), likely driven by the increase between individual stages (note Br 2 elevation compared to Br 0, p < 0.01). The use of the Alz-50 antibody may be confounded by its cross-reactivity with an uncharacterised developmentally regulated protein (Foetal Alz-50-reactive 1 clone protein, FAC1) [14], thus tau conformational changes were further probed with the related MC-1 antibody, which does not cross-react with FAC1 [37]. MC-1 immunoreactivity was distinct from that of Alz-50, detecting a highly selective signal in AD cf. Non-AD cases (Fig. 3bi + ii, p < 0.0001) and was enhanced in accordance with grouped Braak stages (Fig. 3biii, p < 0.0001), principally derived from the level of reactivity within the high category (low cf. high: p < 0.001; intermediate cf. high: p < 0.01). A strong correlation with MC-1 positive conformational tau and Braak stage was apparent (Fig. 3b, r = 0.60, p < 0.0001), and determined as elevated from ≥Br 4 relative to Br 0 (p < 0.05).

Fig. 3 Conformational and oligomeric tau pathology. a Alz-50 and b MC-1 conformational tau and c oligomeric tau (tau-oligomeric-complex 1; TOC1) dot blots. The inset (C) illustrates an example Western blot for TOC1 run under non-reducing, non-denaturing conditions, labels show diagnosis status (C = non-AD and AD). In A–C, quantifications of immunoreactivity is categorised according to diagnosis (ii), severity (iii, low: Br 0–2, intermediate (Inter): Br 3–4 and High: Br 5–6) and correlation with Braak stage (iv). Significances are indicated as follows: *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001 and Spearman’s correlation (r). The lowest Braak stage at which immunoreactivity was significantly elevated from Braak 0 is indicated by $ Full size image

In addition to the emergence of conformational tau pathology, formation of oligomeric tau species has been proposed to correlate with behavioural deficits in animal models [7] and was also previously reported to be elevated in human AD cases [40, 64, 79]. TOC1 binds to a conformation-dependent epitope preferentially exposed upon oligomerisation (aa209–224) [79], and here recognised a single band when tested in Western blot applications under non-denaturing conditions (no DTT or boiling, ~180 kDa; Fig. 3c i, for full blot see Supplementary Figure 2). This band was previously established via SELDI-TOF MS as a tau dimer [63]. TOC1 immunoreactivity was characterised in all cases via native state dot blots (Fig. 3cii) and robustly increased for AD compared to non-AD cases (Fig. 3ciii, p < 0.0001), significantly tracked across grouped Braak stages (Fig. 3civ, p < 0.0001) and correlated with individual Braak stage (Fig. 3cv, r = 0.59, p < 0.0001). Relative to Braak stage 0 a significant elevation in reactivity emerged at Braak stage 5 (p < 0.05), although in a subset of cases a strong signal prior to this was apparent (Br 4 cf. Br 0, p = 0.07).

Correlations of tau biomarkers

Correlative analysis of each pathological tau marker within our soluble preparation demonstrates a variable degree of agreement between all tau markers, with the exception of Alz-50 (Table 2). Interestingly, prominent markers for conformational and oligomeric tau yielded high correlations with differential phosphorylation epitopes (MC-1 with PHF-1 and TOC1 with CP13). No correlation with PMI, cortical pH or age was observed with any of the markers tested; this was further confirmed by ANCOVAs (all p’s > 0.05).

Table 2 Correlations of tau pathology markers Full size table

APP processing and pathology

Amyloidogenic processing

Immunoblotting with the commonly used antibody 6E10, which is raised towards the human Aβ 1-16 sequence, produced multiple bands in Western blots corresponding to various APP metabolites as well as full-length APP (fAPP). The major 6E10 immunoreactive band migrated between 80 and 120 kDa and was consistently observed in lysates from human samples and a hAPP overexpressing mouse (Fig. 4a i). This primary band equates to various post-translational modified species of fAPP and was evidently reduced between AD and non-AD cases (Fig. 4a ii, p < 0.05) but failed to reach significance across grouped Braak stages (Fig. 4a iii, p = 0.09). Levels of fAPP did, however, correlate (negatively) with the progression of Braak stage (Fig. 4a iv, r = −0.39, p < 0.01); post hoc analysis indicated this to be due to a significant reduction in the levels of fAPP as early as Braak stage 2 (p < 0.05 for Br 2 vs Br 0). Similar trends for the reduced expression of fAPP were also observed following the use of an N-terminal APP directed antibody (see Supplementary Figure 3).

Fig. 4 Amyloid precursor protein cleavage. Exemplary Western blots for a full-length APP detected via 6E10 immunoreactivity, and b β-secretase (BACE1) are illustrated. Braak stage (Br) and diagnosis (non-AD (C) cf. AD) are stated above each sample. Positive (+ve) control: human APP overexpressing mouse and negative (−ve) control (in a: wild-type C57/BL6 mouse and in b: BACE1−/− mouse) are included. Total protein normalised immunoblot signals were analysed according to diagnosis (ii), severity (iii, low: Br 0–2, intermediate (Inter): Br 3–4 and high: Br 5–6) and Braak stage correlation (iv). Statistical results are presented as *p < 0.05, **p < 0.01 and Spearman’s correlation (r) are stated in the graphs. $ indicates the lowest Braak stage at which immunoreactivity differed significantly from Braak 0 Full size image

The reduction of fAPP with diagnosis and disease severity may suggest a facilitation of APP cleavage via amyloidogenic secretases in AD cases. Several groups have previously reported a disease-dependent increase in BACE1 and thus a promotion of Aβ production pathways [24, 34]. However, despite the decrease of fAPP, BACE1 expression levels were unaltered in any of the analytical stratifications (Fig. 4b; p > 0.05 for all).

Aβ species

The detection of Aβ species, from monomers to oligomers, is problematic due to a number of confounding factors such as the cross-reactivity of many Aβ-directed antibodies with similar-sized non-Aβ APP metabolites and the potential for experimental parameters to modify Aβ self-oligomerization [80]. Probing standard Westerns blots with 6E10 detected immunoreactive bands migrating at 4 kDa equating to monomeric Aβ and 12 kDa band potentially equating to trimeric Aβ or C-terminal fragments of APP. The 12 kDa band was not quantified here, but also was detected in lysates from hAPP overexpressing mice, yet absent in wild-type mouse lysates (see example in Fig. 5a i). Initial quantification of monomeric Aβ (all cases), demonstrated a ~6-fold increase in monomeric Aβ levels in AD relative to non-AD cases (Fig. 5a ii, p < 0.0001) and an overall effect of grouped Braak stages (Fig. 5a iii, p < 0.001). Post hoc analysis demonstrated that significance was principally driven by the elevation at late stages (Br ≤ 2 cf. Br ≥ 5, p < 0.001 and Br 3–4 cf. Br ≥ 5, p < 0.001). Interestingly, a strong correlation with Braak stage was also established (r = 0.57, p < 0.0001) but the increased Aβ immunoreactivity did not reach significance from Braak stage 0 until stage 5 (p < 0.01).

Fig. 5 Monomeric β-amyloid (Aβ). Immunoblot for a monomeric Aβ (6E10 antibody). Diagnosis (Non-AD (C) cf. AD) and Braak stage is stated for each case. Positive (+ve) control: human APP overexpressing mouse and negative (−ve) control (wild-type mouse) samples are also shown. Size comparison was established via a Coomassie stained low molecular weight protein ladder (insert). Quantification was conducted either for all cases (b) or only for samples where a band was evident (c), the percentage (%) of cases in which monomeric Aβ was detected is stated below the graph. Total protein adjusted immunosignal stratified to i) diagnosis ii) severity (Low: Br 0–2, Intermediate (Inter): Br 3–4 and High: Br 5–6) and iii) correlation with individual Braak stage. Significances are illustrated as ***p < 0.001, ****p < 0.0001, Spearman’s correlation is also stated. $: indicates the earliest Braak stage at which immunoreactivity was higher than that observed at Braak stage 0 Full size image

Quantification of monomeric Aβ based on all cases is questionable as it relies on the inclusion of data from samples lacking a discernible band (i.e. signal value near background). The absence of detectable soluble Aβ in mildly dissociated tissues (manual homogenisation as opposed to sonification) using Western blots has previously been established [38], therefore, quantification in this fashion cannot be considered technically robust. Others have employed direct measurements using densitometry (for example [49, 67]), but failure to adjust for inter-blot differences in background and signal intensity may introduce additional noise into the data. More appropriate analysis arises from monomeric Aβ levels quantified only for those samples in which a band can be clearly detected (16 out of 19 AD samples, 14 out 27 non-AD samples). With this approach (termed monomeric Aβ positive, Fig. 5c i), monomeric Aβ was confirmed to be elevated for AD diagnosed cases relative to Non-AD controls (p < 0.01) and demonstrated a significant effect of grouped Braak staging (Fig. 5c ii p < 0.001), yet post hoc analysis demonstrated only a significant elevation between Braak stage 3–4 and 5–6 (p < 0.001) but not Braak stages 0–2 (p > 0.05). Normalisation of the data set to Braak stage 2 was not possible due to the inconsistent detection of monomeric Aβ within cases of low-stage pathology. Other higher molecular Aβ aggregates have attracted attention in the past, for example, the frequently reported dodecameric Aβ*56 [48, 49]. A corresponding band was detected here following longer exposure times, which revealed several additional bands on Western blots probed with 6E10 (Fig. 6a). In a subset of cases (n = 16), we attempted to quantify and validate the *56 band. Although no significant difference between diagnosis or severity groups could be established (Fig. 6b i–ii), an apparent decline in *56 levels with Braak stage was observed (Fig. 6b iii) in agreement with previous reports [49]. However, Western blot protocols pose several technical issues for the identification of Aβ oligomers due to species modifications induced by reducing agents and heating of samples. Therefore, samples were also run under quasi non-denaturing conditions as conducted for TOC1. Under these near-native state conditions (Fig. 6a), the detection of *56 was greatly diminished and no consistent alteration was observed in any analytical stratification for any group (Fig. 6a + c), indicative that potential artefacts induced by standard SDS-PAGE methods had likely modified native Aβ species.

Fig. 6 Heat-dependent detection of Aβ oligomers. a Side by side comparison of 6E10 immunoreactivty following boiling and non-boiling of samples prior to SDS-PAGE separation. Monomeric, trimeric and *56 Aβ bands are indicated alongside individual diagnosis (C non-AD control and AD cases) and Braak stage (Br) classifications. Quantification of *56 oligomeric Aβ levels according to i) diagnosis, ii) severity (Low: Br 0–2, intermediate (Inter): Br 3–4 and High: Br 5–6) and iii) correlation to individual Braak stage for boiled (b) and non-boiled (c) samples Full size image

As an alternative means of quantifying soluble Aβ load, non-denaturing dot blots were stained with the Aβ-selective antibody MOAB-2, which does not cross-react with APP or other metabolites [77]. Here, Aβ was consistently detected in all AD cases, with levels robustly elevated in diagnosed relative to Non-AD samples (Fig. 7a ii, p < 0.0001); the signal increased progressively across grouped Braak stages (Fig. 7a iii, p < 0.0001). Further statistical comparison revealed strongest elevations in Braak 5–6 cases compared to Braak 0–2 (p < 0.001) and Braak 3–4 (p < 0.05). The progressive increase in soluble Aβ load was further confirmed by the positive near-linear correlation of MOAB-2 reactive species with Braak stage (Fig. 7a iii, r = 0.71, p = 0.0001). MOAB-2 levels were initially detected as enhanced at Braak stage 3 relative to Braak stage 0 (p < 0.05).

Fig. 7 Soluble Aβ detection. Example immunoblots for a i) MOAB-2 and b i) pyro-glu reactive Aβ; each case is labelled with corresponding diagnosis [Non-AD (C) cf. AD] and Braak stage. Quantified signals normalised to total protein are shown stratified to ii) diagnosis iii), severity (Low: Br 0–2, Intermediate (Inter): Br 3–4 and High: Br 5–6) and iv) correlation with Braak stage. *p < 0.05, ***p < 0.001, ****p < 0.0001 and Spearman’s correlation r is stated in iv. $ denotes lowest Braak stage at which immunoreactivity differed from Braak 0 Full size image

Next, cases were further probed for post-translational modification of Aβ species with pyro-glu [21]. In Western blots, a single immunoreactive band was identified migrating ~12 kDa, which in a subset of samples approached significant elevations based on diagnosis and when samples grouped in low, intermediate and high Braak stages (p = 0.07 and p = 0.08, respectively), but did correlate with individual Braak stages (r = 0.32, p < 0.05; data not shown). When all cases were characterised in non-denaturing immuno-dot blot conditions, pyro-glu Aβ immunoreactivity was enhanced based on diagnosis criteria (Fig. 7b i, p < 0.05), increased in line with grouped Braak stages (Fig. 7b ii, p < 0.05) and correlated with individual Braak stage (Fig. 7b iii, r = 0.32, p < 0.05). Post hoc analysis indicated that significance was largely driven by late-stage pathological changes (Br 5–6 cf. Br ≤ 2, p < 0.05), yet no individual Braak stage was significantly elevated from Br 0 cases. As can be seen in scatter plots in Fig. 7b, significance was primarily driven by two highly reactive AD cases, however, further investigation (Grubb’s outlier test) did not report these as significant (p > 0.05).

To further characterise the impact of heating on Aβ and their detection, boiled and unboiled lysates were transferred onto nitrocellulose membranes. Under boiling conditions, the diagnosis-specific increase of Aβ as detected by MOAB-2 was abolished and even appeared reduced relative to Non-AD cases (Fig. 8a i–ii, p = 0.09). The heat-sensitive nature of MOAB-2 mediated Aβ detection was further confirmed by a two-way ANOVA, comparing across grouped Braak stages (Fig. 8a iii, Braak stages: F (2,26) = 0.83, p > 0.05, boiling: F (1,26) = 5.9, p < 0.01 and interaction: F (2,1) = 3.8, p < 0.05). In comparison, the detection of phospho-Tau was unaffected by boiling (see Supplementary Figure 4).

Fig. 8 Heat sensitivity of soluble Aβ (MOAB-2 epitope). (i) Dot blots of either boiled or non-boiled samples probed with MOAB-2 for oligomeric Aβ. Diagnosis [non-AD (C) and AD] and Braak stage (Br) are shown for each sample. Matched samples for boiled vs non-boiled conditions were analysed according to diagnosis (ii) and severity (low: Br 0–2, intermediate (Inter): Br 3–4 and high: Br 5–6) (iii). Statistical outcome of a two-way ANOVA is reported in the corresponding graph. *p < 0.05 and ***p < 0.001 Full size image

Correlation between Aβ-related biomarkers

The various Aβ-related markers failed to demonstrate a similar interrelated pattern as observed for tau (Table 3). Nevertheless, fAPP measurements inversely correlated with quantified levels of MOAB-2 reactive Aβ, which itself correlated with monomeric and pyro-glu Aβ, as one would expect for a signal derived from a metabolite of APP. No correlation or effect of cortical pH or PMI as covariates was observed for any of the Aβ markers examined here (p > 0.05).

Table 3 Correlations between amyloid pathology markers Full size table

Tau and Aβ: mutual correlations

The correlations identified for tau and amyloid markers imply a relationship of components within the categories of tau and amyloid species. Determining correlations between these pathologies is of critical importance, particularly in light of the early stage emergence of both soluble tau and amyloid (Table 4). Accordingly, soluble MOAB-2 reactive Aβ was the only Aβ-related marker to correlate with all markers of tau pathology, and best matched with phospho-tau markers PHF-1 and AT8 (r > 0.63, p < 0.0001 for both). These observations were further strengthened by the reciprocal, inverse correlations of oligomeric (TOC1), conformational (MC-1) and phospho-tau (CP13 and AT8) with total fAPP. In contrast to soluble MOAB-2-reactive Aβ, monomeric Aβ and pyro-glu Aβ correlated more selectively with phospho-tau and oligomeric tau epitopes.

Table 4 Correlations between tau and amyloid markers Full size table

Pathological correlates of Braak staging and cognition

The overall robust correlations of both tau and Aβ markers with Braak stages are summarised in Table 5 and listed alongside associations obtained with cognitive measures. Outcomes were in close agreement with each other, reporting strong correlations with all phospho-tau markers but also with conformational tau (MC-1) and oligomeric tau (TOC1). Critically, for amyloidogenic processing soluble MOAB-2 reactive Aβ consistently reported a high level of correlation with cognitive decline, approximately matching the correlative strength of tau markers. Monomeric Aβ also strongly correlated with cognitive decline, however, this must be viewed with caution due to the lack of reliable detection in some AD cases.