Part 2:Part 1:Entorhinal Tau Pathology, Episodic Memory Decline, And Neurodegeneration in Aging
Mar 19, 2022
Contact: Audrey Hu audrey.hu@wecistanche.com
Robust correlations did not reveal a significant association between PiB DVR and episodic memory (r 0.07, [ 0.23, 0.09]) in either A (r 0.00, [ 0.27, 0.29]) or A subjects (r 0.22, [ 0.52, 0.13]; Fig. 2A). Associations of episodic memory with age and entorhinal thickness across all subjects were not significant (seeTable 2for CIs;Fig. 2B). If subjects were divided by A status, age was related to memory in the A subjects (r 0.35 [ 0.58, 0.07]) but not the A subjects (r 0.07 [ 0.27, 0.41]). HC volume was positively related to episodic-memoryperformanceacrossallsubjects(r 0.24[0.01, 0.43])andinA subjects(r 0.33[0.07,0.54]),butnotinA subjects (r 0.02 [ 0.26, 0.31]).
We also assessed correlations between episodic memory and tau-tracer uptake separately for visual (spatial figure) and verbal (word list) recall memory (Table 2). Verbal memory showed sig- nificantassociationswithAV-1451SUVRinbothBraakcompos- ite ROIs (BraakI/II r 0.25 [ 0.43, 0.07], BraakIII/IV r 0.27 [ 0.44, 0.08]) but with none of the other variables. We note that there was also no significant relationship between ver- bal episodic-memory and volume or thickness measures when these were assessed separately for left and right hemisphere, al- thoughcorrelationstrengthwashigherfortheleftside(EC: rleft 0.19 [ 0.02, 0.40]; rright 0.02 [ 0.18, 0.23]; HC: rleft 0.20 [ 0.01, 0.40]; rright 0.05 [ 0.18, 0.25]). Visual memory was also related to AV-1451 SUVR in all Braak ROIs (BraakI/II r 0.38 [ 0.53, 0.20], BraakIII/IV r 0.31 [ 0.51, 0.11]) as well as to HC volume (r 0.23 [0.02, 0.39]). The relationship between visual memory and HC volume was most robust if vol- umes were averaged across hemispheres (rleft 0.17 [ 0.04, 0.36], rright 0.19 [ 0.02, 0.36]).
To assess the specificity of the relationship between tau-tracer uptake and episodic memory in our population, we also examined associations with executive function and working memory. The executive-function composite score was not significantly related to AV-1451 SUVR in any Braak ROI (Table 2) in either the Aorin the A subjects. Also, working memory did not show a significant relationship with tau-traceruptakeinanyBraakROI (Table 2) in any of the groups. For associations of executive function or working memory with age, PiB DVR, and MRI measures, see also table 2.
Braak/II tau is the best predictor of memory
We performed stepwise linear regression analyses to identify which set of variables best predicted episodic memory in our elderly participants. Our set of predictors included age, PiB DVR, AV-1451 SUVR in BraakI/II and BraakIII/IV ROIs, HC volume, and entorhinal thickness. Braak/II SUVR was the best predictor of episodic memory (F(1,81) 20.8, r2adj 0.194, p 0.001, ANOVA; Model 1 inTable 3) with no other variable significantly improving the model. The only other variable that was marginally significant was HC volume (t(81) 1.7,p 0.09), which may share variance with AV-1451 SUVRs for a number of reasons, including PVC. Other demographic variables, such as gender (t(81) 1.49,p 0.14) or education (t(81) 0.61, p 0.54), also did not significantly account for additional variance.
Table3.GLMspredictingepisodicmemorybytau,A,andtheirinteraction
We then ran GLMs to test whether there was an interaction effect between A and BraakI/II tau on episodic memory (Table 3). In a model that only included main effects of both biomarkers (Model 2., F(2,80) 10.6, r 0.190, p 0.001, ANOVA), BraakI/II SUVR significantly predicted memory (B 1.91, SE 0.53,p 0.001) even when accounting for PiB DVR (B 0.36, SE 0.46, p 0.44). In a model that comprised BraakI/II SUVR, PiB DVR and their interaction term (Model 3., F(3,79) 7.0, r 0.180, p 0.001, ANOVA), the interaction was not significant (B 0.34, SE 1.91, p 0.86). We note that there was also no evidence for an interaction between A and BraakI/II tau on episodic memory when A was defined as a categorical variable (interaction: B 0.57, SE 0.97, p 0.56; A: B 0.83, SE 1.27,p 0.52; Braak I/II SUVR: B 1.78, SE 0.66, p 0.001). This is also reflected by the finding that the slopes for the linear regression of memory on BraakI/II SUVR were similar between A subjects(slope2.35, r2 0.18,F(1,45) 9.97,p 0.003) and A subjects (slope 1.78, r2 0.19, F(1,34) 8.21, p 0.007). We note that results were consistent when using non- PV-corrected BraakI/II mean SUVRs.
Age and A independently predict increased BraakI/II tau We further tested how global A and age were related to tau- tracer uptake in BraakI/II and BraakIII/IV ROIs. The association between PiB DVR and AV-1451 SUVR in BraakI/II and BraakIII/IV composite ROIs is illustrated in Figure 3A. In A subjects, higher PiB DVR was related to higher AV-1451 SUVR in BraakI/II ROIs (r 0.51 [0.23, 0.73]), whereas the association did not reach significance in BraakIII/IV ROIs using robust correlations (r 0.32 [ 0.01, 0.62]). In A subjects, there was no signifi- cant relationship between PiB DVR and AV-1451 SUVR in any Braak ROI (BraakI/II r 0.05 [ 0.24, 0.36]; BraakIII/IV r 0.11 [ 0.17, 0.39]). The association between age and AV-1451 SUVR in BraakI/II and BraakIII/IV composite ROIs is illustrated inFigure
3B. In A subjects, higher age was related to higher AV-1451 SUVR in BraakI/II ROIs (r 0.40 [0.06, 0.63]), but not in BraakIII/IV ROIs (r 0.23 [ 0.06, 0.51]). There was no significant relationship between age and AV-1451 SUVRs in A sub- jects(BraakI/II r 0.00[ 0.30,0.33]; BraakIII/IV r 0.07[ 0.26, 0.42]), but we note again that the age range was smaller in this group (69–86 years).
GLMs showed that both PiB DVR and age were significant (independent) predictors for BraakI/II SUVR (F(2,80) 16.2, r 0.27, p 0.001, ANOVA; PiB DVR: B 0.42, SE 0.08, p 0.001; age: B 0.01, SE 0.003, p 0.01), although the effect size for age was small (Table 4). To summarize at this point, episodic memory was best predicted by BraakI/II SUVR, which increased with both higher age and higher PiB DVR. Notably, the two PiB subjects with the highest SUVR in BraakI/II regions and the lowest episodic-memory score were both 90 years old.
Entorhinal tau shows the strongest relationship to episodic memory
ROI-based analyses on temporal lobe tau associations with memory
To examine local associations between temporal lobe tau-tracer uptake and memory, we used the FreeSurfer-derived ROIs of the HC, EC, PHC, FuG, ITG, and MTG (Desikan et al., 2006) and subdivided those along the longitudinal axis of the temporal lobe. TheparcellationisschematicallyillustratedinFigure1A and sub-regions are shown for the group T1 template in MNI space in Figure 1B. We used the most anterior, the middle, and the most posterior HC slice (Fig. 2, cut points 1–3) as landmarks to coronally slice each gyrus (PhG, FuG, ITG, MTG) into four segments (ant, med, post, post-HC). A detailed description of the parcellation and labeling (which partly differs from FreeSurfer) is given in the Materials and Methods section. Note that we merged Free-Surfer EC and PHC ROIs before parcellation to derive a continuous PhG ROI. Our PhG and PhGmed segments correspond to the anterior and posterior EC, respectively, whereas the PhGpost segment corresponds to the PHC. We ran robust correlational analyses between memory performance and bilateral (i.e., left and right hemisphere averaged) AV-1451 SUVR values derived from each temporal lobe subregion in subject space after PVC and in MNI space (CIs adjusted for multiple comparisons).
Absolute skipped Pearson correlation coefficients for the association between temporal lobe SUVRs derived from subject space and episodic memory are displayed as a heat map inFigure 4A. Episodic-memory composite scores were significantly associated with AV-1451 SUVRs in all PhG regions, comprising anterior EC ( PhGant, r 0.39 [ 0.63, 0.10]), posterior EC ( PhGmed, r0.41[ 0.62, 0.14]),and PHC( PhGpost, r 0.37 [ 0.60, 0.10]). Furthermore, the correlation was significant with the posterior FuG (FuGpost, r 0.37 [ 0.63, 0.08]). Notably, the LiG, which joins the PhG posteriorly, did not show a significant correlation with memory (r 0.18, [ 0.45, 0.04]). Scatterplots for the association between memory and all three segments of the PhG as well as the LiG are illustrated inFigure4B.Associationsbetweentau-traceruptakeinPhGsub- regions and episodic memory were significant in both A and A subjects (Fig. 4B).
The non-PV-corrected MNI space data revealed a similar pattern with the strongest correlation between episodic memory and tau-tracer uptake found with the posterior EC (r 0.43 [ 0.67, 0.14]; all other r’s 0.36; data not shown).
Moreover, these findings were consistent across modalities with the posterior EC SUVR showing strongest associations with verbal recall memory (r 0.37 [ 0.60, 0.08], all other r’s 0.33) and visual memory (r 0.50 [ 0.69, 0.26], all other r’s 0.32) compared with other temporal lobe regions. This is shown in Figure 4C.
The ITG is a region of particular interest, as it shows strong differences in tau PET signal between AD patients and controls (for review, see Saint-Aubert et al., 2017). We compared the as- sociationbetweenepisodicmemoryandAV-1451meanSUVRin EC versus ITG by means of a percentile bootstrapping approach (Wilcox, 2016; see Material and Methods). We found that the correlation of episodic memory with the EC was significantly stronger than with the ITG mean SUVR (r 0.13 [ 0.24 0.02], p 0.02, one-sided 0.05).
Whole-brain voxelwise analyses on tau–memory associations
WealsoperformedvoxelwiseregressionsinMNIspacetofurther examines the spatial pattern of memory–tau associations in the whole brain and confirms our ROI-based findings. Predicting episodic memory by AV-1451 tau-tracer uptake revealed four significant clusters, all located in the medial or lateral temporal lobe (cluster(FWE) 0.05, voxel(core) 0.001, no explicit mask). The global maximum was located in the left lateral EC at the transition toward the perirhinal cortex at the rostrocaudal level of the anterior HC head (Fig. 5, blue cross). The cluster covered the posterior EC as well as parts of the anterior EC and PHC. The same region was significant on the right side. Furthermore, significant voxelwise relations were found with regions in left medial to posterior IT Gandle ftposteriorMTG.Peak coordinates are summarized inTable 5.
Entorhinal-thickness atrophy closely mirrors tau pathology
Fifty-seven of 83 OAs had longitudinal MRI as well as cognitive data (2 scans/testing sessions). Longitudinal MRI data comprised 5 scans over a period of 4.5 2.6 years and an average delay of 2 years between scans. Longitudinal cognitive data comprised 10 sessions over a period of 5.6 2.5 years and an average delay of 1 year between sessions. More details about the longitudinal data can be found in Materials and Methods. In this subsample, we assessed the relationship of entorhinal-thickness change with AV-1451 SUVR, PiB DVR, and episodic-memory change. We used all available MRI data and cognitive data to derive slopes by means of linear mixed-effects models. The AV- 1451 tau scan was acquired between 2.7 years before to 0.7 years after the last MRI and similarly between 2.8 years before to 0.7 years after the last cognitive session. For 40% of subjects, the tau scan was acquired after or at the time of the last MRI scan, such that atrophy data were fully retrospective. Regarding the cognitive data, in 30% of subjects, measures of memory decline were fully retrospective to the tau scan.
We found that entorhinal-thickness changes were strongly correlated with BraakI/II SUVRs (r 0.60 [ 0.78, 0.36];Fig. 6A), whereas the relationship with BraakIII/IV ROIs was not sig- nificant (r 0.15 [ 0.38, 0.11]). Notably, entorhinal-atrophy measures were related to BraakI/II tau measures in both A (r 0.53 [ 0.82, 0.08], n 28) and A subjects (r 0.64 [ 0.82, 0.34], n 29). When using non-PV-corrected data, correlation strength was lower (OA: r 0.40 [ 0.63, 0.15];
A :r0.45[ 0.80,0.02];A :r0.42[ 0.69, 0.05]), although still significant across the whole group (data not shown). GlobalPiBDVRwasnotsignificantlyrelatedtoentorhinal-thickness change(r0.11[ 0.33,0.14]).Entorhinal-thicknesschangewas also correlated with change in episodic memory (r 0.33 [0.09, 0.54];Fig. 6A). Similarly, BraakI/II SUVR was related to change in episodic memory(r0.37[ 0.55, 0.17];Fig.6A).Wenotethat in accordance with our cross-sectional analyses on episodic- memory performance (Fig. 2A), change in memory was related to BraakI/II SUVRsinbothA (r0.41[ 0.55, 0.17])andA (r 0.61 [ 0.78, 0.29]) subjects.
Furthermore, we assessed the regional specificity of associations betweenECatrophyorepisodic-memory decline and temporal lobe tau PET tracer retention. A heat map displaying skipped Pearson coefficients across all temporal lobe subregions, derived by parcellation as described in the preceding text, is depicted in Figure 6B. Correlations between EC-thickness change and AV-1451 SUVR were only significant in the MTL (r 0.46) including the PhG and HC subregions as well as the amygdala (all other r’s 0.29). The correlation between EC-thickness change and AV-1451 SUVR was strongest in the posterior EC (PhGmed, r 0.58
[ 0.75, 0.34]), the same region that showed the strongest associations with episodic memory in the full sample (Fig. 4). Notably, this pattern of associations between entorhinal atrophy and tau measures being confined to MTL subregions was consistent when using non-PV-corrected SUVRs, although correlations were slightly weaker. Similarly, episodic-memory change was negativelyrelatedtoAV-1451SUVRinMTLregions(r 0.40) including the PhG, amygdala, anterior HC, and FuGmed (ROI that includes the perirhinal cortex). The pattern of associations between temporal lobe tau-tracer retention and memory change was similar to cross-sectional associations (Fig. 4A) but with involvement of amygdala and HC in addition to the EC and PHC. In summary, we found strong local associations between entorhinal-thickness atrophy and in vivo tau pathology, which closely mirrored the relationship between tau and cross-sectional as well as longitudinal measures of episodic memory.
Discussion
We investigated how age and in vivo measures of regional tau, global A burden, and MTL atrophy contribute to episodic-memory performance in cognitively normal elderly. We found that tau-tracer uptake in BraakI/II regions comprising the EC and HC best explained episodic-memory performance, with no additional value from any other variable. There was no interaction of AandBraakI/II tauonmemory.Associationsoftautracerretention with episodic memory were strongest in the EC and present in subjects with and without evidence of A accumulation. In A subjects, higher MTL tau PET measures were related to an older age. Furthermore, entorhinal tau measures were linked to entorhinal atrophy and episodic memory decline in subjects with longitudinal MRI and cognitive data. Our findings are consistent with neuropathological data that showed a close relationship between NFTs in PhG and memory impairments across OAs and patients (Mitchell et al., 2002). Our data also extend previous results by showing that effects of tau on memory are independent of several additional variables, most notably A, that there is regional specificity to this relationship, particularly involving the EC/transentorhinal cortex, and that tau deposition is related to longitudinal EC atrophy. Together, our data, obtained during life, suggest that entorhinal tau pathology and related atrophy underlie memory impairments typically seen in old age even in the absence of A. This findingsofanA-independent / age-dependent tau pathy related to cognition is consistent with the concept of PART (Josephs et al., 2017; Crary et al., 2014).
Several previous PET studies in samples that included AD patients reported associations between episodic memory and tau- tracer uptake in the MTL, whereas global cognition was associated with tau in wider neocortical regions (Cho et al., 2016a; Ossenkoppele et al., 2016; Maass et al., 2017). Brier et al. (2016) studied associations between tau and A PET topographies and cognition in a sample of controls and mildly impaired patients. Their data revealed tau PET as the dominant topography contributing to episodic memory. However, they found that the tau topographies were sparse, comprising mostly temporal regions, for all domains except memory, where the topography covered broader neocortical regions. In a small sample of 18 A OAs, Shimada et al. (2016)reported voxelwise associations (at an un- corrected threshold) between logical memory and 11 [C]PBB3 tau-traceruptakeintheHCandseveralcorticalregions.Whether the relationship between memory and tau measures is constrained to the MTL or seen with wider neocortical areas is likely related to the sample, with patients that bear more widespread tau pathology and more severe memory impairments often driving associations.
Our temporal lobe parcellation revealed the strongest associations between episodic memory and tau-tracer retention in the PhG, most prominently in the posterior EC. This was true across memory modalities.Voxel-wise analyses confirmed these findings and showed that the peak for the memory–tau PET associations was located in the left lateral EC at the transition toward the perirhinal cortex at the rostrocaudal level of the anterior HC head. A similar area showed the strongest correlation on the right side. Braak and Braak defined the transentorhinal area on a section that included the HC at the uncle level and a full description of its anterior-posterior extent is lacking. Notably, our EC ROI also covered the medial bank of the collateral sulcus, and thus likely included the transentorhinal area. Due to the low resolution of our PET data (6–7 mm isotropic), we cannot dissociate the lateral and medial parts of the PhG. Still, it is striking that among all temporal lobe regions, the EC—the first cortical region where NFTs accumulate—was most strongly linked to episodic memory. This association was most prominent in the posterior part of EC, but also present in neighboring regions, such as the anterior EC and PHC. MRI studies with higher imaging resolution may shed more light on dysfunction or atrophy of entorhinal subregions (Maass et al., 2015; Olsen et al., 2017; e.g., anterolateral vs posteromedial) in relation to in vivo tau pathology.
TheECisamajorcorticalhub (Botaetal.,2015) mediates HC-neocortical communication and is critical to memory formation. On the one hand, episodic-memory decline is one of the earliest cognitive signs of AD dementia and entorhinal atrophy is a sensitive marker that predicts the conversion from “normal aging” to AD (Killiany et al., 2002; Desikan et al., 2009). High-resolution MR imaging has shown the most significant volume and thickness differences between MCI patients and older controls in the left BA35, corresponding to the transentorhinal region (Yushkevich et al., 2015). The BA35 was also the only region where thickness measures discriminated A from A OAs (Wolk et al., 2017). Olsen et al. found reductions in anterolateral EC volume, including the transentorhinal area, in clinically normal OAs “at-risk” for MCI due to low cognitive performance (2017).EvidenceforearlymetabolicdysfunctioninthelateralEC in preclinical AD is supported by diminished perfusion in those adults that progress to AD (Khan et al.,2014).On the other hand, transentorhinal tau pathology, and decreased episodic-memory performance are common in clinically normal elderly. Fjell et al. (2014)found similar rates of entorhinal thinning in participants with a very low probability of incipient AD compared with a bigger sample of OAs, and the changes were predictive of changes in memory. This suggested that EC thinning in advanced age, even in areas vulnerable to AD, can be part of a “normal” aging process.
Since tau pathology is age-related, accumulates early in the MTL, and relentlessly progresses in the course of AD (Braak and Braak, 1997), it is reasonable to assume that deterioration of memory function is present in both cognitively normal elderly and in AD dementia. In our study, high entorhinal tau measures, along with entorhinal atrophy, and low memory performance were presentinsubjectswithandwithoutA(the latter being concordant in the concept of PART). Our data cannot unravel whether those individuals are on a path toward AD. In the current view, this transition is characterized by the spread of tau tangles outside the MTL, whichseemstorequirethepresenceofA, and leads to worsening of global cognition (Sperling et al., 2014).
Our data did not support any link between tau or A PET measures either with working memory, confirming findings by Brier et al. (2016), or with executive function in normal elderly. This is in accordance with a meta-analysis that did not reveal evidence for associations between PiB measures and working memory or executive function in cognitively normal OAs (Hed- den et al., 2013). Effects of A and tau pathology on executive function or working memory may be profound in later stages of AD,whentaupathologyhasspreadtoBraakVareas.WithinOAs without a diagnosis of dementia, gray and white matter degradation of frontal-striatal networks is thought to be the major cause underlying deficits in executive function (Buckner, 2004; Hed- den and Gabrieli, 2004).
Regarding episodic memory, BraakI/II tau-tracer retention ac- counted for 20% of the variance in our data. Measures of MTL
structure, A burden, age, gender, or education did not explain additional variance in the memory performance. In a neuropathological study on the contributions of A load, NFT density, in- facts, and Lewy bodies to cognitive decline in OAs, only tangles accounted for an episodic-memory decline when all pathologies were considered simultaneously (Boyle et al., 2013b). Furthermore, the pathologic indices of AD, cerebrovascular disease, and Lewy body disease together explained only 41% of the variance in global cognitive decline (Boyle et al., 2013a). Hedden and colleagues found that multiple in vivo brain markers (structural measures, white matter hyperintensities, fractional anisotropy, functional connectivity, and PET measures of glucose metabolism and A) together accounted for 20% of the variation in episodic memory. These data indicate that while many different variables underlie memory decline, a large proportion of late-life cognitive variance remains unexplained, even when neuropathological data are available. Other potential factors forage-relate variability in memory function include changes in the dopaminergic system that primarily target frontal-striatal networks
To summarize, tau-tracer uptake in a region coinciding with the location of the transentorhinal cortex predicted episodic- memory performance in our cohort of cognitively normal OAs independent of A status. Furthermore, tau measures and episodic- memory decline were tightly linked to entorhinal atrophy. Our data suggest that entorhinal tangle pathology is a major factor contributing to memory decline in old age. While A might accelerate tau pathology within and initiate spread outside the MTL, it does not seem to underlie age-related memory de- cline. Longitudinal tau and A PET data are necessary to better understand the causal and temporal link between both pathologies and to elucidate which factors predict the conversion toward AD.
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