Cerebellar Reference Research Articles

Multi‐cohort temporal modeling of tau PET onset age and trajectories

AbstractBackgroundSampled iterative local approximation (SILA) is a temporal modeling method previously validated in three cohorts to estimate person‐level amyloid PET onset age and predicted change. This study validates SILA to model longitudinal tau PET trajectories, generate person‐level estimated tau onset age (ETOA), and characterize forward and backward prediction accuracy in the Wisconsin Registry for Alzheimer’s Prevention (WRAP), Wisconsin Alzheimer’s Disease Research Center (WADRC), and the Alzheimer’s Disease Neuroimaging Initiative (ADNI).MethodN=273 participants (mean(SD) baseline age=70.79(6.70)) from WRAP and WADRC underwent longitudinal 18 F‐MK‐6240 tau PET imaging. Data processing included Harvard‐Oxford ROI parcellation of T1‐weighted MRI and generation of regional MK‐6240 standard uptake volume ratios (SUVR; inferior cerebellar GM reference region; 70‐90 min). Volume‐weighted SUVR corresponding to the meta‐temporal composite (MTC) was averaged across amygdala, parahippocampal gyrus, temporal fusiform cortex, inferior‐temporal, and middle‐temporal bilateral ROIs. Gaussian mixture modeling was applied to baseline SUVR to establish tau positivity (T+) thresholds (MK‐6240 SUVR>1.39; FTP SUVR>1.36) 2SD above the mean of the lower distribution. Ten‐fold cross validation was used to characterize forward and backward SUVR prediction and T+/‐ stratification accuracy. Forward prediction was evaluated by predicting SUVR at each person’s last observation inputting each person’s first observation whereas backward prediction used the last observation to predict SUVR at the first observation. Results were compared with SILA validation using UC‐Berkeley processed ADNI Flortaucipir data with similar processing methods.ResultSILA exhibited similar prediction accuracy and midpoint conversion error in Wisconsin and ADNI studies. Figure 1B/D depicts MTC‐tau onset‐age‐aligned trajectories in Wisconsin and ADNI cohorts, respectively. Backward SUVR prediction error was lower and T+/‐ stratification accuracy was higher than forward prediction (ADNI RMSEforward=0.12, ADNI RMSEbackward=0.08; WI RMSEforward=0.22, WI RMSEbackward=0.17; forward accuracy=0.90, 0.92; backward prediction accuracy=0.96, 0.98 for ADNI and WI, respectively; Table 1). In the T‐ to T+ converters subset, backwards ETOA confidence intervals were within ‐2.68 to 2.04 years of midpoint between the observed last negative and first positive scan (Figure 2).ConclusionSILA provides replicable estimates of T+ onset age and similar prediction accuracy with MK‐6240 and FTP. Future work will investigate how sources of tau PET variability influence temporal modeling outcomes.

Longitudinal stability of extra‐cerebral off‐target binding in [F‐18]MK6240 PET images

AbstractBackgroundThe spread of tau in Alzheimer’s Disease (AD) can be tracked in vivo using [F‐18]MK6240, a PET radioligand that binds to tau aggregates in AD with high affinity. However, significant MK6240 signal is also observed in the meninges and sinus and the extra cerebral binding (ECB) signal from these regions can spill into exterior brain regions complicating evaluation of early stage AD tauopathy. This study evaluates the magnitude and variability of ECB in a large imaging cohort to identify trends in this signal.MethodParticipants included in this study were imaged at the University of Wisconsin–Madison on a Biograph mCT (n = 488) or ECAT HR+ (n = 475) PET scanner including 208 with longitudinal data taken an average of 2.0±1.0 years apart. Reconstructed PET images were smoothed using a 6mm3 gaussian kernel then processed using a standardized pipeline to generate SUVR images using the inferior cerebellar grey matter reference region. Meninges and sinus SUVR were compared across demographic groups of interest within the cohort and longitudinal changes in signal were quantified using the absolute change from baseline to follow up scans.ResultsWhile there were not significant differences in ECB signal seen with age (pmeninges= 0.89, psinus= 0.98), amyloid (pmeninges= 0.43, psinus= 0.95) or tau statuses (pmeninges= 0.18, psinus= 0.35) a significantly higher average SUVR in the meninges and sinus for female (pmeninges< 0.001, psinus< 0.001) and APOE4+ participants (pmeninges= 0.007, psinus= 0.05) was observed. Longitudinally there was an average absolute SUVR difference between scans of 0.21±0.34 (12.1±10.9%) in the meninges and 0.24±0.33 (12.9±10.4%) in the sinus. This is more than triple the average longitudinal SUVR variability of 0.06±0.06 (6.5±6.0%) in the entorhinal region in our amyloid negative participants. APOE4+ participants additionally showed a significantly higher absolute change in the meninges (p = 0.05), however, the increase in the sinus was not significant (p = 0.59).ConclusionsMK6240 ECB can be highly variable and has the potential to bias tracer uptake outcomes. While we observed trends related to sex and genetic risk factors, further work to identify the underlying sources and correct for ECB is ongoing.

Estimating the time between Aβ positivity and elevated regional tau in preclinical AD

AbstractBackgroundUnderstanding when Aβ positive cognitively normal individuals develop tau pathology has important implications for treatment with anti‐Aβ therapies. We employed a changepoint regression approach to estimate time from Aβ‐PET positivity to regionally elevated tau‐PET in a population‐based cohort of primarily cognitively unimpaired individuals.MethodParticipants from Insight 46 (1946 British birth cohort) underwent two [18F]florbetapir Aβ‐PET scans and a sub‐sample enriched for Aβ were also scanned with [18F]MK‐6240 tau‐PET, characteristics are presented in Table 1. Age at Aβ‐PET positivity, defined through Gaussian mixture modelling (GMM) as >12 Centiloids, was estimated using the SILA algorithm (Betthauser et al. 2022). Tau‐PET SUVRs from a temporal‐meta, Braak I‐VI and 34 bilateral FreeSurfer7 regions were calculated 90‐110 mins post‐injection using an inferior cerebellar grey matter reference region. Tau‐PET positivity cutpoints for each region were defined using the 99th percentile of the lower distribution from GMM. For each region, we tested changepoints in the slope of the linear regression between tau‐PET SUVR and time from estimated Aβ positivity with Bonferroni correction (5% significance, p<.001).ResultAt tau‐PET scan, 90 individuals (60%) were >0 years from estimated Aβ positivity. There was a statistically significant difference in slopes before and after the changepoint for all composite regions excluding Braak VI (Figure 1). Changepoint estimates show that tau accumulation started ∼2.5yrs after estimated Aβ positivity in Braak stages I‐III; and ∼10‐12.5yrs for Braak stages IV‐V, and the temporal‐meta region (Figure 2A). Regional estimates broadly followed Braak stages for 16/36 regions showing significant evidence of change in slopes (Figure 2B). Tau positivity rates before changepoints did not exceed 5%, whereas post‐changepoint tau positivity rates were between ∼10% and ∼50%. Regions with later changepoints tended to exhibit higher post‐changepoint slopes with greater uncertainty.ConclusionElevated tau‐PET signal occurs ∼2.5 years after estimated age of Aβ onset in Braak stages I‐III and ∼10‐12.5 years in temporal‐meta and Braak stages IV‐V, with uncertainty within these groupings. These estimates for later Braak stages are consistent with results from previous work on the timing of positive tau PET visual reads. These findings may have implications for determining the optimal time to administer Aβ immunotherapies in asymptomatic individuals.

Linking the estimated time of onset of low locus coeruleus integrity to the estimated time of onset of elevated entorhinal tau

AbstractBackgroundEstimating the time course of locus coeruleus integrity changes is important for a better understanding of the pathophysiological cascade and for identifying the optimal window of opportunity for prevention trials. We used samples iterative local approximation (SILA) to determine the individual estimated time of onset of low LC integrity and related this to early cortical tau deposition and cognitive decline.Methods101 individuals from the Harvard Aging Brain Study+ with longitudinal 3T MRI‐LC imaging, 18F‐Flortaucipir (FTP)‐PET imaging (n=92 with longitudinal data), longitudinal cognitive assessments and baseline PiB‐PET imaging were included (mean age: 69.97 years (SD: 12.46); 62 females; Table 1). LC intensity was derived by normalizing the LC to the pontine reference and averaging 5‐voxel‐clusters with the highest intensities (GMM‐based cut‐off: <1.34 = LC+). FTP‐burden was quantified in the entorhinal cortex (cerebellar grey reference region, partial volume corrected, GMM‐based cut‐off: >1.41 SUVr = EC+). SILA was used to model trajectories of LC intensity and EC FTP separately. Time to onset of LC+ was correlated with baseline entorhinal tau and neocortical amyloid. Repeated measures correlations related the time to onset to LC+ to longitudinal entorhinal FTP and longitudinal PACC scores. Time to onset to LC+ and elevated EC+ were correlated to each other.Results75.25% (n=76) of the individuals were considered LC+ (Figure 1A) and 40.22% (n=37) was EC+ (Figure 2A). Being closer to the LC+ time to onset was correlated with higher entorhinal FTP (r=0.34, p<0.001), but not with neocortical PiB (r=0.09, p=0.42; Figure 1B‐C). Moving closer to the time to onset to LC+ was associated with faster accumulation of entorhinal FTP (r=0.40, p<0.001), and faster cognitive decline (r=‐0.39, p<0.001; Figure 1D‐E). The LC+/EC+ onset trajectories were positively correlated (r=0.23, p=0.025; Figure 2B), and 36% of the individuals was LC‐EC‐, 3% LC‐EC+, 50% LC+EC‐ and 36% LC+EC+, and the time between LC+EC‐ to LC+EC+ was 6.06 years (SD:3.15; Figure 2C).ConclusionsLC integrity imaging allows for temporal modeling and our data suggests that LC integrity precedes accumulation of entorhinal tau by on average 6 years. Future work will evaluate the impact of risk and protective factors on these trajectories.

Improved Disease Subtyping and Staging using Dual Biomarker Amyloid PET

AbstractBackgroundData‐driven disease progression models of Alzheimer’s disease (AD) have identified subtypes in regional patterns of Aβ deposition using amyloid PET. In addition to Aβ accumulation, early frame measures of tracer delivery from amyloid PET are strongly correlated with blood flow. This work explores whether combining tracer delivery with amyloid binding measures can improve the subtype and stage characterisation over amyloid binding alone.MethodsData was included from participants in three studies: Insight46, a neuroimaging sub‐study of the Medical Research Council National Survey of Health and Development (n=405), AVID2, a study of patients with a differential diagnosis of Alzheimer’s Disease (n=15), and YOAD, a study of patients with clinically diagnosed young onset Alzheimer’s disease (n=15). All participants underwent a full dynamic 18F‐Florbetapir PET/MR scan. PET images were reconstructed from 0‐2 and 40‐50 minutes post injection to generate the tracer delivery and amyloid binding images, respectively. T1 parcellations were used to calculate regional standardised uptake value ratios (SUVRs) using a cerebellar grey matter reference region. Tracer delivery and amyloid binding SUVRs for 6 cortical regions were converted into z‐scores, assuming unimodal and bimodal distributions respectively, and modelled using subtype and stage inference (SuStaIn). Participants fitted as stage zero were excluded.ResultsFigure 1 shows the three subtypes found using regional amyloid binding SUVR. Subtype 2 accumulates amyloid first in the occipital lobe, while for subtypes 1 and 3, which accumulate Aβ first in the precuneus and insula respectively, this is the last area to show Aβ deposition. Two distinct subtypes were found with blood flow SUVR; frontal or precuneus first blood flow reduction, Figure 2. When both measures are combined, Figure 3, the data show that subtypes 1 and 2 exhibit amyloid accumulation before blood flow changes, whereas subtype 3 shows blood flow changes in all regions first. The two blood flow subtypes are spread across all three combined subtypes, suggesting that each amyloid subtype may have several blood flow subtypes.ConclusionsCombining blood flow and amyloid SUVR within SuStaIn reveals new patterns of disease progression compared to amyloid alone. This may help us better understand heterogeneity in aging and disease.

Comparison of reference region stability for longitudinal amyloid PET in Down syndrome

AbstractBackgroundThe cerebellum is frequently used as the reference region for amyloid PET analysis. However, this reference region has been shown to demonstrate longitudinal variability, particularly with [18F]florbetapir (FBP) PET (Landau, JNM 2015). For investigations in individuals with Down syndrome (DS), cerebellar atrophy and rapid disease progression may increase these longitudinal variabilities. Although white matter possesses different non‐displaceable uptake properties, the relative lack of specific binding makes white matter a suitable reference region for longitudinal studies. This work compares the observed longitudinal change when using whole cerebellum and white matter reference regions in [18F]FBP and [11C]PiB scans of adults with DS.MethodParticipants with DS, recruited through the ABC‐DS study, underwent longitudinal PiB or FBP PET imaging and T1w MRIs (Table 1 lists cohort differences). PET images were smoothed to 8mm resolution, summed 50‐70 min, co‐registered with the MRI, and normalized to a common DS MRI template (LeMerise, 2022). GAINN whole cerebellum (WC) VOI was applied to create SUVRWC. Whole brain white matter was segmented in native space using SPM, smoothed to PET resolution, and eroded to 90% tissue probability. The resulting eroded white matter (EWM) mask was used as reference to create SUVREWM. Average SUVR was calculated for GAINN global cortex (CTX). Longitudinal scans were assessed for correlations between reference region strategies and average rate of SUVR change: % Change/year = (SUVR2‐SUVR1)/(SUVR1*Δt).ResultFigure 1 displays the averaged EWM reference template. Figure 2 displays longitudinal PET data and regressions between SUVRs. Across participants, SUVRWC shows 78/90 (PiB) and 50/83 (FBP) between‐scan increases. SUVREWM shows 66/90 (PiB) and 71/83 (FBP) between‐scan increases. For A+ individuals (18CL cutoff), the average difference (% ChangeEWM ‐ % ChangeWC)/year is ‐0.5%/year [‐1.2,0.3] (PiB) and 1.9%/yr [0.5,3.3]** (FBP). FBP group SD in % Change/year decreases from 5.6% (WC) to 2.9% (EWM).ConclusionAs observed in LOAD, SUVREWM demonstrates lower group variability and greater longitudinal change in FBP. SUVREWM shows strong agreement with SUVRWC in PiB. These data suggest that an EWM reference region can reduce variability in longitudinal FBP studies in DS.

Plasma pTau217, gender, and synaptic density

AbstractBackgroundSynaptic loss is a key feature of Alzheimer’s disease (AD) dementia. In the entorhinal cortex (ERC) and hippocampus, phosphorylated tau (pTau) colocalizes with synaptosomes, and its presence may play a role in AD‐related synaptic loss. However, the relationship between pTau and synaptic density is not well understood. Plasma pTau represents secreted tau pathology and among the available epitopes, pTau217 has emerged as an accurate biomarker of AD pathology. Here, we tested the relationship between secreted pTau217 and synaptic density.MethodParticipants were recruited from the Wisconsin Alzheimer’s Disease Research Center and the Wisconsin Registry for Alzheimer’s Prevention (N=38; Table 1). All participants underwent blood sampling for measurement of plasma pTau217 and [C‐11]UCB‐J PET to assess synaptic density in regions of interest (ROIs: hippocampus, ERC, and fusiform gyrus) known to show early AD tau accumulation. Synaptic density was quantified using [C‐11]UCB‐J DVR (LGA, whole cerebellar reference region) and ROIs were identified following FreeSurfer T1w‐MRI parcellation. Plasma pTau217 was determined using the ALZpath pTau217 Simoa assay on the Quanterix HD‐X platform. We utilized multiple regression analysis to examine the extent to which plasma pTau217 and gender predict synaptic density in ROIs controlling for age. All models were fitted in R and considered significant at Bonferroni‐corrected (.05/3) p<.017. During analysis we discovered one outlier; a cognitively‐unimpaired participant with pTau217 concentration >2.5 standard deviations above the mean and high UCB‐J DVR in all ROIs. Results with and without the outlier were considered.ResultPlasma pTau217 (b=‐.07, p=0.01) and gender (b=‐.05, p=0.008) predicted UCB‐J DVR in the hippocampus, but not other ROIs (Table 2). The effect size of plasma pTau217 and gender, as measured by Cohen’s f2, was 0.23 and 0.34, respectively, indicating medium to large effects. Welch’s t‐test showed a significant gender difference in hippocampal UCB‐J DVR (Figure).ConclusionOur results indicate that higher levels of plasma pTau217 associated with lower synaptic density in the hippocampus. However, given the individual with high pTau217 and synaptic density, it is possible other processes unaccounted for in this analysis are impacting this relationship. Further examinations could give insight into early processes that confer neuronal injury in the AD pathological cascade.

The prevalence of tau‐PET positivity in aging and dementia

AbstractBackgroundTau‐PET imaging allows in‐vivo detection of neurofibrillary tangles. One tau‐PET tracer (i.e., [18F]flortaucipir) has received FDA‐approval for clinical use, and multiple other tau‐PET tracers have been implemented into clinical trials for participant selection and/or as a primary or secondary outcome measure. To optimize future use of tau‐PET, it is essential to understand how demographic, clinical and genetic factors affect tau‐PET‐positivity rates.MethodThis large‐scale multi‐center study includes 9713 participants from 35 cohorts worldwide who underwent tau‐PET with [18F]flortaucipir (n=6420), [18F]RO948 (n=1999), [18F]MK6240 (n=878) or [18F]PI2620 (n=416) (Table 1). We analyzed individual‐level tau‐PET SUVR data using a cerebellar reference region that were processed either centrally (n=3855) or by each cohort (n=5858). We computed cohort‐specific SUVR thresholds based on the mean + 2 standard deviations in a temporal meta‐region of amyloid‐negative cognitively normal (CN) individuals aged >50. Logistic generalized estimating equations were used to estimate tau‐PET‐positivity probabilities, using an exchangeable correlation structure to account for within‐cohort correlations. Analyses were performed with (interactions between) age, amyloid‐status, and APOE‐ε4 carriership as independent variables, stratified for syndrome diagnosis.ResultThe study included 5962 CN participants (7.5% tau‐PET‐positive), 1683 participants with mild cognitive impairment (MCI, 33.8% tau‐PET‐positive) and 2068 participants with a clinical diagnosis of dementia (62.1% tau‐PET‐positive) (Figure 1). From age 60 to 80 years, the estimated prevalence of tau‐PET‐positivity increased from 1.2% [95% CI: 0.9%‐1.5%] to 3.7% [2.3%‐5.1%] among CN amyloid‐negative participants; and from 16.4% [10.8%‐22.1%] to 20.5% [18.8%‐22.2%] among CN amyloid‐positive participants. Among amyloid‐negative participants with MCI and dementia, from age 60 to 80 years, the estimated prevalence of tau‐PET‐positivity increased from 3.5% [1.6%‐5.3%] to 11.8% [7.1%‐16.5%] and from 12.6% [4.5%‐20.7%] to 15.9% [6.7%‐25.1%] respectively. In contrast, among amyloid‐positive participants with MCI and dementia, from age 60 to 80 years, the estimated prevalence of tau‐PET‐positivity decreased from 66.5% [57.0%‐76.0%] to 48.3% [42.9%‐53.8%] and from 92.3% [88.7%‐95.9%] to 73.4% [67.5%‐79.3%] respectively. APOE‐ε4 status primarily modulated the association of age with tau‐PET‐positivity estimates among CN and MCI amyloid‐positive participants (Figure 2).ConclusionThis large‐scale multi‐cohort study provides robust prevalence estimates of tau‐PET‐positivity, which can aid the interpretation of tau‐PET in the clinic and inform clinical trial designs.

Associations of cerebral amyloid and tau with neurocognitive performance: Findings from the 90+ Study

AbstractBackgroundAssociations between cognition and brain markers of amyloid, tau, and neurodegeneration are poorly understood in the oldest‐old (>90 years) compared to younger populations. Prior work suggests that the link between neuropathology and cognition may become weaker in advanced old age, reducing the applicability of accepted biomarker cascade models of Alzheimer’s disease progression. Addressing this question in the oldest‐old is challenging, partly due to limited data and methodological challenges of neuroimaging analysis. In this study, we examine the associations of (1) cerebral amyloid and tau, (2) amyloid and cognitive performance, and (3) tau and cognitive performance, in the overall group and as stratified by amyloid positivity.MethodParticipants were from the oldest‐old cohort from the 90+ Study at University of California, Irvine (N=98; mean age at assessment=92.04 years; %female=53,). We used MRI‐free analyses of PET imaging to investigate the relations among amyloid (AV45), tau (AV1451) in Braak regions 1/2, 3/4 and 5/6, and cognitive measure (Mini‐Mental State Exam [MMSE]). Native PET images were warped directly to an appropriate PET template, yielding SUVRs computed using cerebellar reference means. Amyloid positivity used an SUVR cutoff of 1.11, computed over a standard index region. All regressions were controlled for age, sex, education, and Apolipoprotein E status.ResultGroup characteristics are in Table 1. In the amyloid positive group (N=61), we found significant associations for amyloid with tau in Braak 1/2 (p=0.03; Figure 1), and MMSE (p=0.045; Figure 2). Associations of MMSE with tau Braak regions varied (Braak 1/2: p=0.086, Braak 3/4: p=0.018, Braak 5/6: p=0.061; Figure 3). We observed no significant associations in the full cohort or in the amyloid negative group.ConclusionMRI‐free PET processing yielded results in the oldest‐old that are consistent with expected relations among amyloid, tau and cognition. Accurate SUVR measurement requires rigorous template registration and quality control. All significant associations occurred in the amyloid positive group, showing expected relations of amyloid to cognition and early Braak stage tau, and tau to cognition, consistent with accepted models. However, small sample size limited our findings. Further studies are needed to clarify the applicability of amyloid‐tau models in this age group.

Alzheimer’s disease APOE neuropathology‐based score, amyloid, and ptau polygenic scores’ association with amyloid PET positivity

AbstractBackgroundAPOE is the greatest genetic risk factor for AD, however, other smaller genetic effects are often ignored. In this work, endophenotype‐informed polygenic scores (PGS) that exclude the APOE region were tested along with a separate, previously published, APOE neuropathology‐based score (APOEscore). The APOEscore serves as a more nuanced quantification of APOE genetic risk that considers the effects of the different haplotypes. PGS and APOEscore were compared to amyloid positivity, determined via PET imaging, which is used as a measure for AD risk and progression.MethodsAlzheimer’s Disease Neuroimaging Initiative (ADNI) participants with genetic data and Florbetapir (18F‐AV‐45) amyloid PET summary SUVR (whole cerebellum reference region) values were included in analyses. Amyloid positivity (A+) was defined as SUVR > 1.11. PGS were calculated using the weights from genome‐wide association studies (GWAS) of CSF Aβ42 (amyloid‐PGS) or ptau181 (ptau‐PGS), after excluding the APOE region (±500kb). APOE effects were accounted for using the APOEscore that was calculated following Deming et al (2023).Results1094 participants (618 A+) were included in the analyses (Table 1). The APOEscore was significantly associated with A+ after accounting for sex and age at scan (OR = 2.931, P = 6.38e‐45; Table 2). The amyloid‐PGS was also significantly associated with A+ (OR = 0.492, P = 0.026), whereas the ptau‐PGS did not quite reach significance (OR = 3.218, P = 0.054). After adding the APOEscore, the effect of amyloid‐PGS on A+ remained but did not quite reach significance (OR = 0.515, P = 0.072) and ptau‐PGS was not significant (OR = 1.845, P = 0.375).ConclusionThese results validate the utility of the APOEscore with PET amyloid as well as the potential value of including non‐APOE genes in quantifying the genetic risk for amyloid accumulation and AD. The significant association between amyloid‐PGS and A+, and near significance after adding the APOEscore, demonstrates the existence of additional genetic effects outside of APOE that have an impact on amyloid accumulation. While the ptau‐PGS did not reach significance, possibly due to sample size, the OR (3.218) was greater in magnitude than the amyloid‐PGS (1/OR = 2.033). Future work will explore these relationships in other cohorts and with other PET AD biomarkers.

Estimating age at Aβ onset in the 1946 British birth cohort: exploring the influence of APOE ɛ4 carriership and sex

AbstractBackgroundCerebral Aβ accumulates decades before symptom onset in AD. Sampled iterative local approximation (SILA, Betthauser et al. 2022) is a technique for estimating time from Aβ positivity (Aβ+) using Aβ‐PET. Here we explore the influence of APOE‐ɛ4 carriership and sex on estimated age of Aβ+ (EAAβ) in primarily cognitively normal individuals from the longest‐running British birth cohort.MethodParticipants in Insight 46 were drawn from the 1946 British birth cohort and underwent combined PET/MR scanning with [18F]florbetapir at two timepoints. Centiloid (CL) values were calculated using a whole cerebellum reference region and partial volume correction. We used Gaussian mixture modelling (99th percentile of lower distribution) to define an Aβ+ threshold of 12 CL. We constructed a CL vs Aβ time curve with SILA from available longitudinal Aβ‐PET scans (n=324, interval=2.4+/‐0.2yrs), which was applied to the whole sample (n=463) to calculate EAAβ. Some scans were below the CL range that could be modelled, and the estimated EAAβ was truncated to the furthest time before onset on the CL vs time curve. Kaplan‐Meyer plots and Cox regression were used to investigate EAAβ and risk of estimated Aβ+ by APOE‐ɛ4 and sex, right censoring participants where EAAβ was truncated.ResultMean (SD) chronological age was 70.6+/‐0.7yrs at baseline and 73.0+/‐0.6yrs at follow‐up scan and 30.5% were Aβ+ve by follow‐up (n=141, 55.3% APOE‐ɛ4, 51.8% female). SILA results and distribution of EAAβ are shown in Figures 1 and 2. EAAβ were truncated due to low Aβ binding in 35.7% (n=166, 15.7% APOE‐ɛ4, 50% female). APOE ɛ4 carriers reached median EAAβ 8.6 years earlier than non‐carriers (Figure 3A). Median EAAβ for females was marginally earlier than males with overlapping CIs (Figure 3B). APOE‐ɛ4 was strongly associated with risk of estimated Aβ+ (HR[95%CI] = 2.4[1.9,3.0]), adjusted for sex. Female sex (1.1[0.8,1.3]) and the interaction between APOE‐ɛ4 and sex (1.2[0.8,1.9]) were non‐significant.ConclusionEstimated Aβ positivity was reached on average 8.6 years earlier for APOE ɛ4 carriers. Consistent with results from other cohorts, APOE‐ɛ4, not sex, significantly heightened the risk of estimated Aβ positivity. Future research will explore life course and downstream events related to Aβ timing.

Assessment of the relationship between synaptic density and metabotropic glutamate receptors in early Alzheimer's disease: a multi-tracer PET study.

The pathological effects of amyloid β oligomers (Aβo) may be mediated through the metabotropic glutamate receptor subtype 5 (mGluR5), leading to synaptic loss in Alzheimer's disease (AD). Positron emission tomography (PET) studies of mGluR5 using [18F]FPEB indicate a reduction of receptor binding that is focused in the medial temporal lobe in AD. Synaptic loss due to AD measured through synaptic vesicle glycoprotein 2A (SV2A) quantification with [11C]UCB-J PET is also focused in the medial temporal lobe, but with clear widespread reductions is commonly AD-affected neocortical regions. In this study, we used [18F]FPEB and [11C]UCB-J PET to investigate the relationship between mGluR5 and synaptic density in early AD. Fifteen amyloid positive participants with early AD and 12 amyloid negative, cognitively normal (CN) participants underwent PET scans with both [18F]FPEB to measure mGluR5 and [11C]UCB-J to measure synaptic density. Parametric DVR images using equilibrium methods were generated from dynamic. For [18F]FPEB PET, DVR was calculated using equilibrium methods and a cerebellum reference region. For [11C]UCB-J PET, DVR was calculated with a simplified reference tissue model - 2 and a whole cerebellum reference region.. A strong positive correlation between mGluR5 and synaptic density was present in the hippocampus for participants with AD (r = 0.81, p < 0.001) and in the CN group (r = 0.74, p = 0.005). In the entorhinal cortex, there was a strong positive correlation between mGluR5 and synaptic in the AD group (r = 0.85, p <0.001), but a weaker non-significant correlation in the CN group (r = 0.36, p = 0.245). Exploratory analyses within and between other brain regions suggested significant positive correlations between mGluR5 in the medial temporal lobe and synaptic density in a broader set of commonly AD-affected regions. Medial temporal loss of mGluR5 in AD is associated with synaptic loss in both medial temporal regions and more broadly in association cortical regions, indicating that mGluR5 mediated Aβo toxicity may lead to early synaptic loss more broadly in AD-affected networks. In CN individuals, an isolated strong association between lower mGluR5 and lower synaptic density may indicate non-AD related synaptic loss.

Improved Quantification of MicroPET/CT Imaging Using CT-derived Scaling Factors.

Combined micro-PET/CT scanners are widely employed to investigate models of brain disorders in rodents using PET-based coregistration. We examined if CT-based coregistration could improve estimates of brain dimensions and consequently estimates of nondisplaceable binding potential (BPND) in rodent PET studies. PET and CT scans were acquired on 5 female and 5 male CD-1 mice with 3-[18F]fluoro-5-(2-pyridinylethynyl)benzonitrile ([18F]FPEB), a radiotracer for the metabotropic glutamate receptor subtype 5 (mGluR5). In the proposed PET/CT (PTCT) approach, the tracer-specific standard volume was dimension-customized to each animal using the scaling factors from CT-to-standard CT coregistration to simplify PET-to-standard PET coregistration (i.e., 3 CT- and 6 PET-derived parameters). For comparison, conventional PET-based coregistration was performed with 9 (PT9) or 12 (PT12) parameters. PET frames were transferred to the standard space by the three approaches (PTCT, PT9, and PT12) to obtain regional time-activity curves (TACs) and BPND in 14 standard volumes of interest (VOIs). Lastly, CT images of the animals were transferred to the standard space by CT-based parameters from PTCT and with the scaling factors replaced with those from PET-based PT9 to evaluate agreement of the skull to the standard CT. The PET-based approaches showed various degrees of underestimations of scaling factors in the posterior-anterior-direction compared to PTCT, which resulted in negatively proportional overestimation of radioactivity in the cerebellum (reference region) up to 20%, and proportional, more prominent underestimation of BPND in target regions down to -50%. The skulls of individual animals agreed with the standard skull for scaling factors from PTCT but not for the scaling factors from PT9, which suggested inaccuracy of the latter. The results indicated that conventional PET-based coregistration approaches could yield biased estimates of BPND in proportion to errors of brain dimensions when applied to tracers for which the cerebellum serves as reference region. The proposed PTCT provides evidence of a quantitative improvement over PET-based approaches for brain studies using micro-PET/CT scanners.

Molecular neuroimaging in dominantly inherited versus sporadic early-onset Alzheimer's disease.

Approximately 5% of Alzheimer's disease patients develop symptoms before age 65 (early-onset Alzheimer's disease), with either sporadic (sporadic early-onset Alzheimer's disease) or dominantly inherited (dominantly inherited Alzheimer's disease) presentations. Both sporadic early-onset Alzheimer's disease and dominantly inherited Alzheimer's disease are characterized by brain amyloid-β accumulation, tau tangles, hypometabolism and neurodegeneration, but differences in topography and magnitude of these pathological changes are not fully elucidated. In this study, we directly compared patterns of amyloid-β plaque deposition and glucose hypometabolism in sporadic early-onset Alzheimer's disease and dominantly inherited Alzheimer's disease individuals. Our analysis included 134 symptomatic sporadic early-onset Alzheimer's disease amyloid-Positron Emission Tomography (PET)-positive cases from the University of California, San Francisco, Alzheimer's Disease Research Center (mean ± SD age 59.7 ± 5.6 years), 89 symptomatic dominantly inherited Alzheimer's disease cases (age 45.8 ± 9.3 years) and 102 cognitively unimpaired non-mutation carriers from the Dominantly Inherited Alzheimer Network study (age 44.9 ± 9.2). Each group underwent clinical and cognitive examinations, 11C-labelled Pittsburgh Compound B-PET and structural MRI. 18F-Fluorodeoxyglucose-PET was also available for most participants. Positron Emission Tomography scans from both studies were uniformly processed to obtain a standardized uptake value ratio (PIB50-70 cerebellar grey reference and FDG30-60 pons reference) images. Statistical analyses included pairwise global and voxelwise group comparisons and group-independent component analyses. Analyses were performed also adjusting for covariates including age, sex, Mini-Mental State Examination, apolipoprotein ε4 status and average composite cortical of standardized uptake value ratio. Compared with dominantly inherited Alzheimer's disease, sporadic early-onset Alzheimer's disease participants were older at age of onset (mean ± SD, 54.8 ± 8.2 versus 41.9 ± 8.2, Cohen's d = 1.91), with more years of education (16.4 ± 2.8 versus 13.5 ± 3.2, d = 1) and more likely to be apolipoprotein ε4 carriers (54.6% ε4 versus 28.1%, Cramer's V = 0.26), but similar Mini-Mental State Examination (20.6 ± 6.1 versus 21.2 ± 7.4, d = 0.08). Sporadic early-onset Alzheimer's disease had higher global cortical Pittsburgh Compound B-PET binding (mean ± SD standardized uptake value ratio, 1.92 ± 0.29 versus 1.58 ± 0.44, d = 0.96) and greater global cortical 18F-fluorodeoxyglucose-PET hypometabolism (mean ± SD standardized uptake value ratio, 1.32 ± 0.1 versus 1.39 ± 0.19, d = 0.48) compared with dominantly inherited Alzheimer's disease. Fully adjusted comparisons demonstrated relatively higher Pittsburgh Compound B-PET standardized uptake value ratio in the medial occipital, thalami, basal ganglia and medial/dorsal frontal regions in dominantly inherited Alzheimer's disease versus sporadic early-onset Alzheimer's disease. Sporadic early-onset Alzheimer's disease showed relatively greater 18F-fluorodeoxyglucose-PET hypometabolism in Alzheimer's disease signature temporoparietal regions and caudate nuclei, whereas dominantly inherited Alzheimer's disease showed relatively greater hypometabolism in frontal white matter and pericentral regions. Independent component analyses largely replicated these findings by highlighting common and unique Pittsburgh Compound B-PET and 18F-fluorodeoxyglucose-PET binding patterns. In summary, our findings suggest both common and distinct patterns of amyloid and glucose hypometabolism in sporadic and dominantly inherited early-onset Alzheimer's disease.

Characterizing brain tau and cognitive decline along the amyloid timeline in Alzheimer's disease.

Recent longitudinal PET imaging studies have established methods to estimate the age at which amyloid becomes abnormal at the level of the individual. Here we recontextualized amyloid levels into the temporal domain to better understand the downstream Alzheimer's disease processes of tau neurofibrillary tangle (NFT) accumulation and cognitive decline. This cohort study included a total of 601 individuals from the Wisconsin Registry for Alzheimer's Prevention and Wisconsin Alzheimer's Disease Research Center that underwent amyloid and tau PET, longitudinal neuropsychological assessments and met clinical criteria for three clinical diagnosis groups: cognitively unimpaired (n = 537); mild cognitive impairment (n = 48); or dementia (n = 16). Cortical 11C-Pittsburgh compound B (PiB) distribution volume ratio (DVR) and sampled iterative local approximation were used to estimate amyloid positive (A+; global PiB DVR > 1.16 equivalent to 17.1 centiloids) onset age and years of A+ duration at tau PET (i.e. amyloid chronicity). Tau PET burden was quantified using 18F-MK-6240 standardized uptake value ratios (70-90 min, inferior cerebellar grey matter reference region). Whole-brain and region-specific approaches were used to examine tau PET binding along the amyloid timeline and across the Alzheimer's disease clinical continuum. Voxel-wise 18F-MK-6240 analyses revealed that with each decade of A+, the spatial extent of measurable tau spread (i.e. progressed) from regions associated with early to late NFT tau stages. Regional analyses indicated that tau burden in the entorhinal cortex was detectable, on average, within 10 years of A+ onset. Additionally, the entorhinal cortex was the region most sensitive to early amyloid pathology and clinical impairment in this predominantly preclinical sample. Among initially cognitively unimpaired (n = 472) individuals with longitudinal cognitive follow-up, mixed effects models showed significant linear and non-linear interactions of A+ duration and entorhinal tau on cognitive decline, suggesting a synergistic effect whereby greater A+ duration, together with a higher entorhinal tau burden, increases the likelihood of cognitive decline beyond their separable effects. Overall, the amyloid time framework enabled a spatiotemporal characterization of tau deposition patterns across the Alzheimer's disease continuum. This approach, which examined cross-sectional tau PET data along the amyloid timeline to make longitudinal disease course inferences, demonstrated that A+ duration explains a considerable amount of variability in the magnitude and topography of tau spread, which largely recapitulated NFT staging observed in human neuropathological studies. By anchoring disease progression to the onset of amyloid, this study provides a temporal disease context, which may help inform disease prognosis and timing windows for anti-amyloid therapies.

Evaluating the Effect of Extra-Cerebral Off-Target Binding in [F-18]MK6240 PET Scans in Early-Stage Alzheimer’s Disease

Abstract [F-18]MK6240 is a PET radioligand with favorable imaging characteristics for measuring tau aggregation in Alzheimer’s disease (AD). In this study we investigated the impact of extra-cerebral off-target binding (ECB) in the meninges and sinus present in [F-18]MK6240 PET scans on quantifying tau burden in preclinical AD. Based on large cohort data from 433 [F-18]MK6240 scans acquired at the University of Wisconsin-Madison, simulations were conducted to examine the range of effects of ECB by varying the ECB profile and input radiotracer concentration curves on areas of early tau accumulation in AD. The range and patterning of ECB in the imaging cohort had high variability between participants, however, 35% revealed moderate to high meningeal signal that could influence quantification. Partial volume effects, which can lead to measured PET signal from neighboring regions influencing signal in adjacent areas of interest, were examined in the simulated images. The simulations demonstrate that signal from the sinus increases the neighboring entorhinal cortex region (ERC) signal and activity detected from the meninges can similarly influence the inferior cerebellar grey matter reference region. ECB effects from the sinus were most prevalent in our cohort, and simulations with the average ECB profile had ERC uptake (SUV) 23% higher than simulations with no ECB. Spill-in effects from the sinus, which increases the medial and ventral temporal cortex SUVR, and spill-in from the meninges into the cerebellar reference region, which leads to a reduction in global SUVR, act in opposite directions, complicating the interpretation of the derived SUVR of [F-18]MK6240 images. These simulation results quantify the effects of ECB in [F-18]MK6240 scans and introduce correction factors to minimize bias of the SUVR measure.

Synaptic density patterns in early Alzheimer's disease assessed by independent component analysis.

Synaptic loss is a primary pathology in Alzheimer's disease and correlates best with cognitive impairment as found in post-mortem studies. Previously, we observed in vivo reductions of synaptic density with [11C]UCB-J PET (radiotracer for synaptic vesicle protein 2A) throughout the neocortex and medial temporal brain regions in early Alzheimer's disease. In this study, we applied independent component analysis to synaptic vesicle protein 2A-PET data to identify brain networks associated with cognitive deficits in Alzheimer's disease in a blinded data-driven manner. [11C]UCB-J binding to synaptic vesicle protein 2A was measured in 38 Alzheimer's disease (24 mild Alzheimer's disease dementia and 14 mild cognitive impairment) and 19 cognitively normal participants. [11C]UCB-J distribution volume ratio values were calculated with a whole cerebellum reference region. Principal components analysis was first used to extract 18 independent components to which independent component analysis was then applied. Subject loading weights per pattern were compared between groups using Kruskal-Wallis tests. Spearman's rank correlations were used to assess relationships between loading weights and measures of cognitive and functional performance: Logical Memory II, Rey Auditory Verbal Learning Test-long delay, Clinical Dementia Rating sum of boxes and Mini-Mental State Examination. We observed significant differences in loading weights among cognitively normal, mild cognitive impairment and mild Alzheimer's disease dementia groups in 5 of the 18 independent components, as determined by Kruskal-Wallis tests. Only Patterns 1 and 2 demonstrated significant differences in group loading weights after correction for multiple comparisons. Excluding the cognitively normal group, we observed significant correlations between the loading weights for Pattern 1 (left temporal cortex and the cingulate gyrus) and Clinical Dementia Rating sum of boxes (r = -0.54, P = 0.0019), Mini-Mental State Examination (r = 0.48, P = 0.0055) and Logical Memory II score (r = 0.44, P = 0.013). For Pattern 2 (temporal cortices), significant associations were demonstrated between its loading weights and Logical Memory II score (r = 0.34, P = 0.0384). Following false discovery rate correction, only the relationship between the Pattern 1 loading weights with Clinical Dementia Rating sum of boxes (r = -0.54, P = 0.0019) and Mini-Mental State Examination (r = 0.48, P = 0.0055) remained statistically significant. We demonstrated that independent component analysis could define coherent spatial patterns of synaptic density. Furthermore, commonly used measures of cognitive performance correlated significantly with loading weights for two patterns within only the mild cognitive impairment/mild Alzheimer's disease dementia group. This study leverages data-centric approaches to augment the conventional region-of-interest-based methods, revealing distinct patterns that differentiate between mild cognitive impairment and mild Alzheimer's disease dementia, marking a significant advancement in the field.

Associations between sex, body mass index and the individual microglial response in Alzheimer’s disease

Background and objectives18-kDa translocator protein position-emission-tomography (TSPO-PET) imaging emerged for in vivo assessment of neuroinflammation in Alzheimer’s disease (AD) research. Sex and obesity effects on TSPO-PET binding have been reported for cognitively normal humans (CN), but such effects have not yet been systematically evaluated in patients with AD. Thus, we aimed to investigate the impact of sex and obesity on the relationship between β-amyloid-accumulation and microglial activation in AD.Methods49 patients with AD (29 females, all Aβ-positive) and 15 Aβ-negative CN (8 female) underwent TSPO-PET ([18F]GE-180) and β-amyloid-PET ([18F]flutemetamol) imaging. In 24 patients with AD (14 females), tau-PET ([18F]PI-2620) was additionally available. The brain was parcellated into 218 cortical regions and standardized-uptake-value-ratios (SUVr, cerebellar reference) were calculated. Per region and tracer, the regional increase of PET SUVr (z-score) was calculated for AD against CN. The regression derived linear effect of regional Aβ-PET on TSPO-PET was used to determine the Aβ-plaque-dependent microglial response (slope) and the Aβ-plaque-independent microglial response (intercept) at the individual patient level. All read-outs were compared between sexes and tested for a moderation effect of sex on associations with body mass index (BMI).ResultsIn AD, females showed higher mean cortical TSPO-PET z-scores (0.91 ± 0.49; males 0.30 ± 0.75; p = 0.002), while Aβ-PET z-scores were similar. The Aβ-plaque-independent microglial response was stronger in females with AD (+ 0.37 ± 0.38; males with AD − 0.33 ± 0.87; p = 0.006), pronounced at the prodromal stage. On the contrary, the Aβ-plaque-dependent microglial response was not different between sexes. The Aβ-plaque-independent microglial response was significantly associated with tau-PET in females (Braak-II regions: r = 0.757, p = 0.003), but not in males. BMI and the Aβ-plaque-independent microglial response were significantly associated in females (r = 0.44, p = 0.018) but not in males (BMI*sex interaction: F(3,52) = 3.077, p = 0.005).ConclusionWhile microglia response to fibrillar Aβ is similar between sexes, women with AD show a stronger Aβ-plaque-independent microglia response. This sex difference in Aβ-independent microglial activation may be associated with tau accumulation. BMI is positively associated with the Aβ-plaque-independent microglia response in females with AD but not in males, indicating that sex and obesity need to be considered when studying neuroinflammation in AD.

Regional correlation analysis between neuronal metabolism and synaptic density using [18F]FDG and [11C]UCB‐J

AbstractBackgroundNeuronal hypometabolism measured with [18F]FDG PET scans can be used to identify neurodegeneration as part of the AT(N) (amyloid, tau, neurodegeneration) framework in AD. PET imaging of synaptic vesicle glycoprotein SV2A using [11C]UCB‐J provides an index of synaptic density, which has been shown to decrease during neurodegeneration. The purpose of this study was to examine the regional relationship between neuronal metabolism and synaptic density in participants across the continuum of AD‐related pathology.MethodParticipants were recruited from the Wisconsin ADRC and the Wisconsin Registry for Alzheimer’s Prevention (WRAP) study. A subset of 13 participants (Table 1) were selected who had completed cognitive testing, structural MR imaging, and PET imaging with the following: [11C]PiB centiloid (CL) for amyloid +/‐ status, [18F]MK‐6240 SUVR for tau +/‐ status, [11C]UCB‐J DVR for regional synaptic density burden, and [18F]FDG SUVR for regional glucose metabolism. UCB‐J and FDG analysis used a whole cerebellum reference region; PiB and MK‐6240 analysis used cerebellar GM reference regions. Inter‐tracer (UCB‐J/FDG) correlations were performed in Freesurfer‐defined bilateral Braak‐associated ROIs (Medial Temporal Lobe [MTL]: entorhinal cortex, hippocampus, and amygdala; Ventral Temporal Lobe [VTL]: fusiform, lingual, and inferior temporal gyri), signature regions of hypometabolism in AD (posterior cingulate, parietal, and frontal cortices) and a region with only marginal hypometabolism in AD (occipital cortex). Associations were determined using Pearson correlations (r).ResultAll ROIs demonstrate a positive association between FDG SUVR and UCB‐J DVR, with r &gt; 0.7 and p &lt; 0.01 (Figure 1). The occipital, frontal, and posterior cingulate cortices demonstrate the strongest correlations (r = 0.84, 0.83, and 0.81, respectively).ConclusionIn cognitively impaired and unimpaired participants showing varying degrees of ß‐amyloid and neurofibrillary tau burden, strong positive correlations are observed in regions associated with AD tau pathology and hypometabolism. Correlations are also observed in regions not typically associated with hypometabolism. This suggests that a relationship may exist between synaptic density and neuronal metabolism in the presence of AD neuropathology.

MK‐6240 tau‐PET in an Aβ‐enriched sample from the 1946 British birth cohort

AbstractBackgroundWe investigated imaging biomarkers of Aß and neurodegeneration in relation to tau‐PET Braak stage in a preclinical birth cohort.MethodCognitively normal individuals enrolled in Insight 46, the neuroimaging sub‐study of the MRC National Survey of Health and Development (1946 British birth cohort), were scanned on combined PET/MR with [18F]florbetapir Aß‐PET at age ∼70 years and again at ∼73 years. A sub‐sample enriched for Aß (Aß+; Centiloid&gt; = 13, hole cerebellum reference) is currently being assessed with [18F]MK‐6240 tau‐PET at age ∼76 years. For this interim analysis, tau‐PET images (90‐110 minutes post‐injection) were co‐registered with T1‐weighted MRI. Anatomical areas were parcellated on the T1 to form Braak regions. Standard uptake value ratios (SUVRs) were calculated using an inferior cerebellar grey reference without partial volume correction. Tau‐PET positivity (Tau+) was defined using Gaussian mixture modelling in each region. Participants were assigned to Tau‐, Braak I‐II, III‐IV or V‐VI groups based on the most advanced Tau+ region. Group differences in baseline Aß (Centiloids), Aß accumulation (Centiloids/year) and hippocampal atrophy rate (%/year) were investigated with Mann‐Whitney U tests.ResultAnalysis included 80 individuals with tau‐PET data (Table 1), 45% of the sample were Aß+ by age 73. Three individuals did not conform to the Braak stage hierarchy (orange triangles, Figure 1). No Aß‐ individuals were Tau+ beyond Braak I. Figure 2 shows baseline Aß, Aß accumulation and hippocampal atrophy rates for Braak stage groups for participants who had data at all timepoints (N = 78). Tau+ individuals (in any Braak region) had significantly higher baseline Aß than Tau‐ individuals. Rate of annual Aß accumulation was higher for Braak III‐IV and Braak V‐VI compared to Tau‐ individuals. Hippocampal atrophy rate was elevated for Braak V‐VI compared to Tau‐, and Braak III‐IV was borderline significant.ConclusionIn this preliminary analysis, tau‐PET positivity beyond Braak I was restricted to individuals who were Aß+ three years prior. Participants with elevated tau aged 76 had increased Aß at age 70. Increased rates of hippocampal atrophy were occurring at least three years prior to tau scanning in individuals with advanced tau pathology. These findings will be updated as more data is acquired.