Standardized Uptake Value Ratio Research Articles

Florbetapir PET Measurements of Amyloid Plaque Deposition are More Closely Correlated with Cross‐Sectional and Longitudinal Cognitive and Clinical Measurements Using a White Matter Reference Region of Interest

AbstractBackgroundWe previously reported stronger associations of FDG‐PET measured glucose hypometabolism with florbetapir PET measured Aβ deposition quantified using Standard Uptake Value Ratio (SUVR) with a cerebral white matter reference region (SUVRwm) compared to the commonly used SUVR with cerebellar reference region (SUVRcrblm) both cross‐sectionally and longitudinally (Wang et al., AAIC 2021). This study compared cross‐sectional and longitudinal associations of SUVRwm and SUVRcrblm with various cognitive/clinical measuresMethodOur study population consisted of 1133 participants from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) including 206 participants clinically diagnosed with AD dementia, 563 with Mild Cognitive Impairment (MCI), and 364 cognitively unimpaired individuals (CU). We computed partial correlation of SUVRwm or SUVRcrblm, covarying out baseline age and years of education, with Mini Mental State Exam (MMSE); Clinical Dementia Rating Scale Sum Boxes and Global (CDR‐SB and CDGlobal); Alzheimer’s Disease Assessment Scale (ADAS11, ADAS13); Auditory Verbal Learning Test – Short Term Memory, Long Term Memory, and Total (AVLT STM, AVLT LTM, and AVLT Total respectively). Steiger’s Z‐test was used to compare SUVRwm and SUVRcrblm correlation coefficient differences with each of these cognitive/clinical measures at uncorrected p = 0.05 significance. Analyses were carried out over all subjects and within each diagnostic group, first for baseline data and then longitudinally.ResultCross sectionally, correlations were significantly stronger with SUVRwm than with SUVRcrblm for all subjects in all cognitive/clinical measures (all p<1.314E‐04) with the strongest correlation of SUVRwmRef with MMSE (r = ‐0.4717 for SUVRwm and r = ‐0.3463 for SUVRcrblm; p = 1.93E‐13). The strongest correlation within AD subjects was found between SUVRwm and MMSE (r = ‐0.1432 for SUVRwm and r = 0.0459 for SUVRcrblm; p = 9.7063E‐04).Longitudinally, stronger SUVRwm correlations than SUVRcrblm with each of these cognitive measures were also observed over all subjects (p<0.05), and significance with CDR‐SB and AVLT Total in AD; with MMSE, ADAS11, ADAS13, CDGlobal, CDR‐SB, AVLT Total in MCI; and with CDGlobal in CU.ConclusionThe use of cerebral white matter reference region for florbetapir PET SUVR quantification demonstrated stronger associations between amyloid deposition and cognitive measures than cerebellar reference region.

Trajectory of MRI and FDG‐PET biomarkers in Alzheimer’s disease

AbstractBackgroundAlzheimer’s disease (AD) has a long preclinical phase, which is hypothesised to start with the accumulation of β‐amyloid (Aβ) plaques, followed by tau neurofibrillary tangles and neurodegeneration. Despite presenting quite different types of information, MRI‐derived volumetric measures and FDG‐PET‐derived metabolism are both commonly used as proxy of neurodegeneration in AD. The aim of this work is to assess the trajectory of both of these biomarkers in AD, relative to time to amyloid‐positivity.Method3289 MRI scans (682 participants) and 2472 FDG‐PET scans (1296 participants) were included from the ADNIGO, 1,2 and 3 cohorts. For MRI scans, total volume was calculated for a meta‐ROI consisting of entorhinal, inferior, middle temporal and fusiform gyri. For FDG‐PET, standardized uptake value ratios (SUVR) were calculated from 30‐60 min post injection for a meta‐ROI consisting of the angular, posterior cingulate and inferior temporal gyri, normalised to the pons. All metrices were transformed into z‐scores using the references values of the Aβ‐negative subjects. Age of amyloid‐positivity was determined by fitting a nonlinear mixed effects model to 3607 Centloid values corresponding to 1690 participants. Next, time to amyloid‐positivity was calculated for each scan. The relationship between time to amyloid‐positivity and (z‐scored) SUVR or cortical volume values was modelled using a non‐linear mixed effects model with spline function and trajectories from both modalities were compared.ResultsBaseline demographics can be found in Table 1. Figure 1 shows the trajectory of amyloid deposition that was used to determine age of amyloid‐positivity. Cortical volume and SUVR showed similar trajectories over time, with steeper decline in both measures after the event of amyloid‐positivity (Figure 2). The overlay of both biomarker trajectories shows that for the meta‐ROI, there is no difference in when these biomarkers become abnormal.ConclusionsThe present results suggest that measures of neurodegeneration from MRI and FDG‐PET scans corresponding to a meta‐ROI, follow very similar trajectories. Future work will investigate if this also holds true for smaller regions of interest.

Validating noninvasive techniques for 11C‐ER176 PET quantification in controls and Alzheimer’s disease patients

AbstractBackgroundNoninvasive yet accurate PET quantification methods are crucial for safe yet meaningful PET studies. [11C]ER176 is a PET radioligand that images neuroinflammation via the 18‐kDa translocator protein (TSPO), which is upregulated in activated microglia and has previously been a PET target in Alzheimer’s disease research. Currently, the gold‐standard method for quantifying ER176 PET is kinetic modeling of the dynamic PET data using the arterial input function (AIF), which is invasive and expensive. The current study explores a pseudo‐reference region (RR) technique to noninvasively quantify ER176 scans to facilitate clinical PET studies.MethodDynamic 90‐min [11C]ER176 PET scans were acquired in 11 participants, 5 controls (5M/0F) and 6 patients (3 MCI‐3M/0F; 3 AD‐2M/1F). Arterial blood data were collected throughout the duration of the scan and were used along with the dynamic imaging data to determine regional total volume of distribution (VT) using the two‐tissue compartment model. Standardized Uptake Value Ratio (SUVR) was calculated by normalizing the radioactivity in each region by that of the reference region (cerebellar gray matter). We explored differences across methods (AIF‐derived VT vs. RR‐derived SUVR) and across groups (controls vs. patients).ResultWithin each group, the outcome measures from AIF and RR methods were well correlated (Controls: R2 = 0.986, p < 0.001; Patients: R2 = 0.983, p < 0.001; Figure 1). Both methods showed greater TSPO expression in patients compared to controls, with mean differences in the medial temporal cortex of 14.99% between groups for VT and 10.65% between groups for SUVR, but lower variance for SUVR compared to VT (Figure 2). Both quantification methods showed similar regional patterns of percent differences between groups, corresponding to tau progression along Braak staging (Figure 3).ConclusionResults suggest that using the cerebellum, which does not accumulate amyloid plaques or tau aggregates until end‐stage disease, as a reference region for [11C]ER176 may be a valid method for quantifying differences between AD patients and controls compared to gold‐standard methodology. Regional increases in neuroinflammation are more reliable for SUVR than VT in AD‐related regions. Ongoing work includes a larger sample size to further validate noninvasive PET quantification.

Social engagement, amyloid burden, and dementia: the Atherosclerosis Risk in Communities (ARIC)‐PET study

AbstractBackgroundAlthough amyloid deposition in the brain is often associated with subsequent dementia risk, not everyone with brain amyloid will develop dementia. This discrepancy illustrates the potential importance that risk factors and lived experiences may have in modifying this association. Compared to participants with low social engagement (SE) in mid‐life, we hypothesized that participants with high mid‐life SE will show a weaker association between amyloid burden and incident dementia.MethodWe included data from 310 non‐demented participants of the Atherosclerosis Risk in Communities (ARIC)‐PET study. Social support and isolation were assessed via interviewer‐administered questionnaires (Visit 2; 1990 – 1992). Based upon categorization of both factors, participants were classified as having high, intermediate, or low mid‐life SE (Table 1). Brain amyloid was evaluated with florbetapir PET (Visit 5; 2011‐2014). Elevated amyloid burden was defined as standardized uptake value ratio (SUVR) >1.2 in the global cortex. Incident dementia cases were identified from visit 5 through 2019 through ongoing surveillance utilizing in‐person neurocognitive testing, informant interviews, and hospitalization codes. Relative contributions of mid‐life SE and elevated florbetapir SUVR to incident dementia, independently and with multiplicative interaction terms, were evaluated with Cox regression models, adjusted for demographics, APOEε4 and vascular risk factorsResultAmong 310 participants, 48 developed dementia (median follow‐up: 4.7 years). Mid‐life SE and elevated SUVR each independently predicted dementia risk but did not interact on a multiplicative scale. Participants with high or intermediate mid‐life SE, relative to low mid‐life SE, were less likely to develop dementia (Table 2). Although the interaction between mid‐life SE and elevated SUVR was not significant, stratified models suggested a stronger association between amyloid burden and dementia in participants with high mid‐life SE (Table 3).ConclusionGreater mid‐life SE was associated with lower odds of developing dementia, independent of elevated SUVR. Although protective, there was no strong evidence for effect modification of mid‐life SE on the association between amyloid and dementia risk. Future longitudinal studies evaluating the potential influence of social factors measured throughout the life course are needed to inform our understanding as to what factors may preserve cognition in the presence of elevated brain pathology.

To Assess Mediation Effects of BIN1 Risk Variant rs6733839 and APOE4 on Alzheimer’s disease Pathology

AbstractBackgroundAlzheimer’s disease (AD) patients carrying T‐allele in the single nucleotide polymorphism rs744373 show higher levels of misfolded tau protein levels, as well as faster accumulation of neurofibrillary tangles (Franzmeier‐2019; Franzmeier‐2022), in addition to established risk gene apolipoprotein E (APOE4). Here we conduct pathway analysis to understand the direct and indirect effects, mediated through amyloid levels, of the rs6733839 T‐allele and APOE e4‐allele on tau.MethodAmyloid‐positive (florbetapir PET) placebo‐arm patients with a clinical diagnosis of AD dementia from four clinical trials (NCT01900665, NCT02791191, NCT02245737, NCT02016560, Table.1) underwent baseline (N = 547) and follow‐up (N = 230) flortaucipir PET scans. Tau burden was assessed using standardized uptake value ratio (SUVr) in AD‐specific region (MUBADA; Devous‐2018) with respect to cerebellum‐crus. We tested direct and indirect effects of BIN1 (rs6733839) and APOE4 on baseline SUVr and change‐from baseline (CFB) in tau‐PET mediated by baseline florbetapir signal. Unstandardized indirect effects were computed for each of 1,000 bootstrapped samples, and the 95% confidence interval was computed by determining the indirect effects at the 2.5th and 97.5th percentiles.ResultBIN1 and age showed significant association with the baseline tau‐PET level (BIN1: ßeta = 0.05, P = 0.05; Age: ßeta = ‐0.03, P<0.001), whereas APOE4 association with the baseline tau‐PET levels was not statistically significant (ßeta = 0.006, P = 0.81). The bootstrapped unstandardized indirect effect of BIN1, age, and APOE4 mediated via baseline amyloid levels was insignificant (BIN1: ßeta = 0.0002, P = 0.92; Age: ßeta = 3.82e−05, P = 0.74; APOE4: ßeta = ‐0.0003, P = 0.86). When evaluated on longitudinal tau measures, the direct effect of APOE4 on CFB in tau‐PET SUVr was significant (ßeta = 0.02; P = 0.01). The direct and indirect effects (mediated via baseline amyloid levels) of BIN1 (Direct: ßeta = ‐0.007, P = 0.215; Indirect: ßeta = ‐0.0007, P = 0.58) and Age (Direct: ßeta = ‐0.0009, P = 0.26; Indirect: ßeta = 0.0001, P = 0.32) were insignificant.ConclusionBIN1 showed significant association with the baseline tau‐PET level whereas APOE‐e4 allele directly affected longitudinal tau buildup independent of amyloid levels. These observations require additional validation using larger datasets and further optimization of the applied methodology is warranted.

Involvement of differential tau pathologies in late‐onset bipolar disorder assessed by PET with 18F‐florzolotau

AbstractBackgroundNeurodegenerative pathologies, including tau depositions, have been implicated in late‐onset depression (LOD), while there is a lack of in‐vivo evidence for the neuropathological basis of late‐onset bipolar disorder (LOBD) despite postmortem findings of cerebral tau accumulations. The current study aimed to assess tau pathologies in LOBD and LOD patients positron emission tomography (PET) with 18F‐florzolotau, a radioligand for Alzheimer’s disease (AD) and non‐AD tau fibrils.MethodsWe studied LOBD and LOD patients who developed the first episode of mania or depression after age 45. Twenty‐one patients with LOBD (68.8 ± 9.6 years old; 11 females), 15 patients with LOD (73.0 ± 5.8 years old; 11 females), and 39 age‐matched healthy controls (HCs) (67.1 ± 9.1 years old; 19 females) underwent tau and amyloid PET scans with 18F‐florzolotau and 11C‐PiB, respectively. Amyloid positivity was determined by a visual read of 11C‐PiB‐PET images, and tau depositions were assessed by calculating standardized uptake value ratios (SUVRs) in 52 regions covering the cerebral grey matter and basal ganglia to the optimized reference tissue. All SUVRs were corrected for age and sex and converted to Z‐score relative to HCs. The positivity and topology of tau pathologies were determined according to the presence of a region with a Z‐score ≥ 2.0.Results 18F‐florzolotau‐PET positivity was observed in 13 LOBD (62%), 7 LOD (47%), and 11 HC (28%) subjects, whereas 4 LOBD, 4 LOD, and no HC individuals were 11C‐PiB‐PET‐positive. A significant difference in the prevalence of tau pathologies was only found between LOBD and HCs (P = 0.043, corrected for multiple comparisons). Tau topologies in the cases with 11C‐PiB‐PET‐positive AD pathologies consisted of predominant frontal (1 LOBD and 3 LODs), lateral temporal (3 LOBDs and 1 LOD), and posterior (1 LOBD) accumulations. Meanwhile, tau pathologies in 11C‐PiB‐negative cases showed predominant frontal (2 LOBDs and 1 LOD), temporal (1 LOBD and 1 LOD), posterior (4 LOBDs and 1 LOD), and basal ganglia (2 LOBDs) localizations.ConclusionOur findings suggest that a significant subset of LOBD patients harbor tau lesions linked to various AD subtypes and non‐AD tauopathies indicative of distinct early‐stage frontotemporal lobar degeneration subcategories.

Impact of reference region on longitudinal florbetapir PET SUVR changes from the API ADAD Colombia Trial

AbstractBackgroundWe previously examined the impact of using a cerebellar, pons, or cerebral white matter (WM) reference region (RR) on the ability of each to distinguish cortical measures of fibrillar amyloid‐(Aβ) deposition with baseline data in unimpaired presenilin (PSEN1) E280A mutation carriers and non‐carriers (NC) from the Alzheimer’s Prevention Initiative Autosomal Dominant Alzheimer’s Disease (API ADAD) Colombia Trial (NCT01998841). In this study, we extend our findings by comparing these RRs on their ability to distinguish longitudinal changes in cortical measures of serial Aβ‐PET scans from the completed clinical trial.MethodWe estimated template‐based (SPM12) cortical mean change using baseline, 2, and 5‐year florbetapir PET standard‐uptake value ratios (SUVRs) with three different RRs (whole cerebellum, pons, and WM) and compared carriers on placebo (placebo‐carriers, n = 82) with NC all on placebo (NC, n = 83). We calculated Cohen’s D with [95% CI] and standard deviation of NC as effect‐sizes for 2 and 5‐year cortical changes. Additionally, we characterized cerebellar Aβ burden in carriers on crenezumab (treatment‐carriers, n = 81), placebo‐carriers, and NC, using our previously reported method targeting the whole cerebellum region‐of‐interest (ROI) with pons as RR to estimate cerebellar‐to‐pons‐SUVRs and compare using a mixed‐model repeated‐measures ANOVA adjusted for age but not multiple comparisons.ResultAs expected, placebo‐carriers had significantly greater SUVR change compared with NC for all three RRs. However, the pons RR was best at detecting 2‐year changes (d = 1.75[1.39‐2.11]), and WM and pons were best at detecting 5‐year changes in cortical‐Aβ levels between placebo‐carriers and NC (pons d = 2.01[1.64‐2.39], WM d = 2.51[2.10‐2.92]). Additionally, treatment‐carriers had higher cerebellar‐to‐pons‐SUVRs compared with placebo‐carriers at baseline and 2‐years, but not 5‐years (p = .034, p = .027,& p = .06,respectively), both carrier groups had higher cerebellar‐to‐pons‐SUVRs compared to NC at each interval(p<.001). Cerebellar‐to‐pons‐SUVRs continued to increase within carrier groups at each interval(5‐year>2‐year>baseline,p<.05) and remained constant within the NC‐group(p>.05).ConclusionUse of pons for 2‐year and WM or pons RRs for 5‐year changes may improve the power to track longitudinal increases and evaluate Aβ‐modifying treatments in 2 and 5‐year studies, in this ADAD population. A cerebellar RR may be confounded by early Aβ deposition in the cerebellum which can artificially reduce average cortical Aβ‐PET SUVRs even in preclinical stages of ADAD.

Synaptic proteins in pre‐symptomatic Alzheimer’s disease: biomarkers for early detection of Cognitive Decline

AbstractBackgroundSynaptic proteins in the cerebrospinal fluid (CSF) may reveal changes in the pre‐symptomatic stages of Alzheimer’s disease (AD), thus may be candidate biomarkers for early detection of the disease.MethodThe PREVENT‐AD cohort includes symptom‐free (upon enrolment) elderly participants who are at risk of developing AD from their family history. We used enzyme‐linked immunosorbent assay kits to assess CSF samples from 129 such participants for the “classical” AD biomarkers total tau, phosphorylated (181) tau and Aβ42. We also used neuroimaging data (MRI, PET) and neuropsychological assessments (MMSE, RBANS) as potential indicators disease progression. We then used in the CSF samples to measure the soluble synaptic biomarkers ADAM 22 (post‐synaptic), ADAM23 (pre‐synaptic). Immunoprecipitated SYT1 (pre‐synaptic) from CSF were analyyzed using high‐resolution selected ion monitoring analyses on a quadrupole–orbitrap mass spectrometer Q Exactive. Statistical analysis of the association of these markers with evidence of disease in analyses were done included sex and APOE e4 status as covariates.ResultAmong participants who remained cognitively unimpaired, we observed significant correlations between baseline CSF ADAM 22 levels and t‐tau (R2 = 0.22, p < 0.0001), p‐tau (R2 = 0.22, p < 0.0001), and Aβ42 (R2 = 0.06, p = 0.01488). We also found similarly suggestive correlations also between CSF ADAM 23, CSF SYT1 and the same disease markers. Covariate analyses suggested little or no variation in the associations between these synaptic proteins with t‐tau and p‐tau by sex, APOE e4 status, negative PET amyloid positivity (standardized uptake value ratio ≤ 1.37) and negative CSF total tau positivity (≤ 335pg/ul). PET amyloid positivity was significantly associated with ADAM22 and p‐tau interactions whereas SYT1 was significantly associated with t‐tau and p‐tau in CSF tau‐positive participants. In linear regression analyses, baseline CSF ADAM22 levels correlated with the language cognitive performance trajectory slopes estimated over the course of 5 to 8 years on the RBANS (R2 = 0.04, p = 0.03912). We found no significant interaction between other baseline CSF synaptic protein levels and other subscales of the RBANS.ConclusionCSF synaptic protein levels show promising correlation with landmark AD proteins and emerging cognitive deficits.

Association between brain amyloid deposition and longitudinal changes of white matter hyperintensities

AbstractBackgroundWhite matter injury had been mostly considered a result of chronic ischemia caused by cerebral small vessel disease. However, recent studies reported that white matter degeneration could also be an important pathophysiological feature in Alzheimer’s disease (AD). This study aimed to identify the relationship between AD biomarkers, particularly amyloid‐beta (Aβ) and tau deposition, with white matter hyperintensities (WMHs) representing cerebral white matter injury.MethodA total 456 older adults aging from 55 to 90 years including cognitively normal and cognitively impaired individuals were recruited from the Korean Brain Aging Study for the Early Diagnosis and Prediction of Alzheimer’s Disease (KBASE) cohort. The participants underwent comprehensive clinical and neuropsychological assessment, [11C] Pittsburgh Compound B PET for measuring Aβ deposition, [18F] AV‐1451 PET for measuring tau deposition, and MRI scans with fluid‐attenuated inversion recovery image for measuring WMH volume. For PET scans, standard uptake value ratio (SUVR) was used for the analyses; combined regions of hemispheric white matter, inferior cerebellum and pons were used as the reference region when obtaining SUVRs. The relationships between Aβ or tau deposition and WMH volume were examined using multiple regression analysis. In this analysis, baseline Aβ or tau were used as independent variables, and baseline as well as change of WMH volume over 2 years were used as dependent variables.ResultBaseline Aβ deposition levels had significant positive association with longitudinal change of WMH volume over 2 years (β = 0.238, p = 0.009), but not with WMH volume at baseline. Baseline tau was not related with any of WMH volume at baseline and longitudinal change of WMH volume over 2 years. We also found significant interaction effect between baseline Aβ deposition level and sex on longitudinal change of WMH volume. Subsequent subgroup analyses showed that high baseline Aβ deposition was associated with increase of WMH volume over 2 years in female (β = 0.427, p = 0.001), but not in male.ConclusionOur findings suggest that Aβ deposition, but not tau, accelerates cerebral white matter injury, particularly in female.

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> = 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.

Changes in cortical thickness along the Alzheimer disease continuum in people with Down syndrome

AbstractBackgroundTriplication of the APP allele in Down syndrome (DS) leads to excess amyloid production and Alzheimer’s disease (AD) related cognitive decline. Key biomarkers (amyloid, tau, neurodegeneration) can identify pathological processes that occur before clinical symptoms and more precisely stage adults with DS along the AD continuum. Previous research has used changes in cortical thickness (CT) as an indicator of neurodegeneration in autosomal‐dominant AD1, but not DS‐related AD. It is unclear when and where cortical thinning occurs along the AD continuum in DS and if these differences are associated with increasing AD pathology.MethodCross‐sectional analysis compared DS participants from the Alzheimer Biomarkers Consortium‐Down Syndrome (106 amyloid‐/cognitively unimpaired, nonclinical, 20% reserved for receiver‐operating characteristic, ROC, analyses; 45 amyloid+/cognitively unimpaired, preclinical; 27 amyloid+/cognitively impaired, clinical) who had amyloid positron emission tomography and magnetic resonance imaging (MRI). Amyloid positivity was defined using standardized uptake value ratio (partial volume corrected) cortical mean values (1.42/1.19 for PIB/AV452) and impairment was based on consensus diagnosis. CT differences between nonclinical and clinical groups were calculated in FreeSurfer v5.3 for multiple thresholds (p<.05/.01/.005/.001/.0005/.0001) using a cluster‐wise false discovery rate of .001, corrected across hemispheres, after controlling for age and sex. CT values were extracted for each threshold and used in ROC analyses (nonclinical reserved participants compared against preclinical and preclinical compared against clinical) to identify key cortical regions that best discriminated amyloid positivity and between unimpaired and impaired.ResultSignificant decreases in parietal and inferior temporal CT were observed between nonclinical and clinical (Figures 1 and 2). ROC analyses identified regions in the left (threshold .05) and right (threshold .005) hemispheres that best differentiated nonclinical from preclinical. Observed area under the curves (AUCs) of .772 and .830 exceeded those previously reported for autosomal‐dominant AD (.547/.540)1. Analyses differentiating preclinical from clinical observed AUCs of .786 for left (threshold .0005) and .770 for right (threshold .0005) hemispheres.ConclusionCT differences primarily within posterior cortical regions differentiated adults with DS by amyloid status and cognitive impairment. CT differences were more diffuse for amyloid positivity but more focal for impairment.1. Dincer (2020). NeuroImage: Clinical, 28, 102491.2. Su (2019). Alzheimer’s Dement, 11, 180‐190.

Association of FDG‐PET with co‐pathologies in autopsy‐proven AD

AbstractBackgroundThe presence of multiple pathologies is the rule and not the exception in Alzheimer’s disease (AD). The goal of this study was to assess whether 18F fluorodeoxyglucose (FDG) PET can provide information about the presence of non‐AD pathologies in autopsy‐proven AD patients.MethodOur cohort included 55 patients with antemortem FDG‐PET and autopsy‐proven intermediate/high ADNC from the UCSF Neurodegenerative Diseases Brain Bank. All patients underwent FDG‐PET. Standardized uptake value ratio (SUVR) images were computed using the pons as reference region. W‐maps (adjusted Z‐score maps) were created, comparing each patient to a group of 187 controls (age range: 20‐96, 40% males). Voxel‐wise correlations were computed to verify the unique contribution of each neuropathology to cerebral hypometabolism, while controlling for age, sex, time between FDG‐PET scan and death, scanner type, Thal and Braak staging, and the presence of all other co‐pathologies. Associations between SUVR values in specific region of interests (ROIs) were also assessed. The ROIs included were the following: Landau AD ROI for AD pathology, Cingulate Island Sign (CIS) for Lewy body disease, Inferior/Medial Temporal Lobe (IMT) and IMT/Frontal Supraorbital (IMT/FSO) ratios for limbic‐predominant age‐related TDP43 encephalopathy neuropathologic change (LATE‐NC).ResultMean age was 63.8 ± 10.5, mean time between FDG and death was 6.2 ± 2.8, and mean MMSE was 21.1 ± 7.1 at the time of PET (Table 1). Group averaged W‐map showed the typical temporo‐parietal AD pattern; hypometabolism in these regions was associated with higher Thal phase and Braak stage (Figure 1). Lewy body disease (LBD), argyrophilic grain disease (AGD), aging‐related tau astrogliopathy (ARTAG), cerebral amyloid angiopathy (CAA) and vascular brain injury (VBI) were associated with hypometabolism in small discrete regional clusters (Figure 2). The Landau AD ROI was associated with both Thal (rs = ‐0.325, p = .015) and Braak stages (rs = ‐0.447, p<.001). The CIS sign was not associated with the presence of LBD (t(53) = 1.01, p = 0.319). Both the IMT (t(53) = ‐2.25, p = .028) and IMT/FSO (t(53) = ‐3.40, p = .001) ratios were associated with the presence of LATE‐NC.ConclusionCo‐pathologies make a relatively small contribution to hypometabolism in patients with intermediate‐high ADNC. Novel biomarkers are needed for precise detection of co‐pathologies.

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

AbstractBackgroundWe investigated imaging biomarkers of Aβ 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 Aβ‐PET at age ∼70 years and again at ∼73 years. A sub‐sample enriched for Aβ (Aβ+; Centiloid> = 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 Aβ (Centiloids), Aβ 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 Aβ+ by age 73. Three individuals did not conform to the Braak stage hierarchy (orange triangles, Figure 1). No Aβ‐ individuals were Tau+ beyond Braak I. Figure 2 shows baseline Aβ, Aβ 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 Aβ than Tau‐ individuals. Rate of annual Aβ 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 Aβ+ three years prior. Participants with elevated tau aged 76 had increased Aβ 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.

The influence of the ApoE genotype on regional amyloid beta progression and interregional correlations in nondemented elderly

AbstractBackgroundPrevious examinations have explored the spatiotemporal pattern of amyloid beta (Ab) deposition, one of the first pathogenic events in Alzheimer’s disease (AD). However, the literature presents with a limited characterization of early spatial Ab progression differences and interregional correlations related to the major genetic AD risk factor, the Apolipoprotein E (ApoE) genotype.MethodThe impact of ApoE genotype on dynamic spatiotemporal Ab patterns was investigated using longitudinal amyloid positron emission tomography (PET) imaging. A first analysis used data of 100 nondemented participants who were characterized as having an Ab increase over time. Standardized uptake value ratios (SUVRs) of 31 cortical and subcortical regions were extracted. Regional average SUVRs were clustered per genotype based on longitudinal trajectory shapes. A second analysis focused on the ApoE genotype impact on interregional correlations of annual change rates in 81 cognitively normal individuals. We explored the difference in the distribution of correlations and performed permutation statistics. All analyses were replicated and validated applying partial volume correction.ResultE4 carriers and noncarriers displayed different regional Ab trajectories. In general, noncarriers displayed a more homogeneous Ab increase over time in comparison to more diverse trajectories in carriers. Six regional clusters ranging from lowest Ab‐baseline values and none‐to‐small increases (cluster 1) to highest Ab‐baseline values and considerable increases (cluster 6) were identified for both carriers and noncarriers. Independent of genotype, cluster 1 contained the amygdala, the medial part of the anterior temporal lobe, the caudate nucleus, the parahippocampal gyrus, the anterior part of the superior temporal gyrus, and the hippocampus. Other clusters differed between genotypes with several regions being assigned to higher Ab‐baseline and higher increase clusters in carriers. The correlational analysis found a distinct pattern in noncarriers with most regions presenting significant positive intercorrelations except for the hippocampus, which demonstrated almost exclusively null‐to‐negative correlations. This pattern was not found in e4 carriers.ConclusionThe results suggested an ApoE genotype impact on the heterogeneity of the spatiotemporal Ab pattern and a dissociative hippocampal role.

Significance of a positive tau pet scan with a negative amyloid pet scan

AbstractBackgroundThe implications of a positive tau (T) Positron Emission Tomography (PET) with a negative beta amyloid (A) PET are not well understood. We investigated cognitive performance in participants who were positive on tau PET but negative on beta amyloid PET.MethodWe evaluated 98 participants from the Mayo Clinic Study of Aging (MCSA) and the Mayo Clinic Alzheimer’s Disease Research Center (ADRC) who were positive for Flortaucipir (FTP) and negative for PiB PET. Participants were classified as A‐ and T+ based on Standardized Uptake Value Ratios (SUVr) of FTP and PiB PET scans, and were matched 2:1 to amyloid negative and tau negative cognitively unimpaired controls from the MCSA. Cognitive test scores were compared between the combined ADRC/MCSA group and MCSA only group. We also examined clinical diagnoses in our cohort. The most common were Alzheimer’s Disease, mild cognitive impairment (MCI), Dementia with Lewy Bodies (DLB) and Frontotemporal dementia (FTD) amongst others.ResultThere were no significant differences in demographic features or PiB SUVr between groups. There were significant differences in APOE genotype between groups. In the combined ADRC/MCSA group, 25% of A‐T‐ and 13% of A‐T+ were APOE e4 carriers (p = 0.016), and in the MCSA only group, 27% of A‐T‐and 10% of A‐T+ were APOE e4 carriers (p = 0.010). In the combined ADRC/MCSA group, the A‐T+ group demonstrated lower performance than the A‐T‐ group on the Mini Mental Status Exam (MMSE) (p<0.001), Wechsler Memory Scale‐Revised Logical Memory I (p<0.001) and Logical Memory II (p<0.001), Auditory verbal Learning Test Delayed Recall (AVLT) (p = 0.004), Category fluency animals (p = 0.005), Category fluency vegetables (p = 0.021), Trailmaking test A (p<0.001), Trail making test B (p<0.001), Wechsler Adult Intelligence Scale‐IV (WAIS‐IV) (p = 0.002), and Unified Parkinson’s Disease Rating Scale part III (UPDRS III) (p = 0.003). In the MCSA only group, the A‐T+ group had lower scores on Logical Memory II (p = 0.022), AVLT delated recall (p = 0.04), and WAIS‐R block design (p = 0.035) compared to the A‐T‐group.ConclusionPositive tau PET in the absence of beta‐amyloid positivity is associated with lower cognitive performance.

Fast accumulators of tau have higher levels of plasma pTau and stronger associations with amyloid in later Braak regions at baseline

AbstractBackgroundAccumulation of tau neurofibrillary tangles in Alzheimer’s disease (AD) follows a stereotypical pattern, known as Braak staging. As individuals show different rates of tau accumulation, depending on their initial stage, this potentially biases drug effects on tau pathology over time. We hypothesized that amyloid would be a driving force behind tau deposition in later Braak regions for those that were at earlier stages of the disease.Method79 individuals (CU: 57, MCI: 21, AD: 1) were recruited from the Translational Biomarkers of Aging and Dementia (TRIAD) cohort. All individuals underwent baseline and 2‐year follow‐up amyloid ([18F]AZD4694) and tau ([18F]MK6240) PET imaging, as well as baseline plasma pTau181, pTau217, and pTau231 assessments. Differences in standardized uptake value ratios between the two timepoints in Braak I‐IV were used to separate fast accumulators of tau from slow accumulators, using the standard deviation of a Young group (n = 13).Pearson R’s were calculated between tau deposition in Braak regions IV‐VI and the neocortical amyloid load at baseline, within both these groups. Furthermore, a voxelwise analysis was performed to identify specific regional differences in amyloid SUVR between slow and fast progressors, while correcting for age, sex, ApoE4 carriership, as well as the individual’s Braak stage. In addition, an independent t‐test was performed to compare the levels of each pTau species at baseline.ResultFast accumulators had stronger increases (p < 0.01) in tau accumulation in Braak region V and VI, compared to slower accumulators. Furthermore, the level of tau deposition in Braak region IV and V was positively associated (p < 0.01) with the amyloid load in the neocortex, but only in the fast accumulator group (figure 1). The voxelwise analysis confirmed that faster progressors had stronger associations with amyloid‐PET (figure 2). Furthermore, those who accumulated tau at a faster rate also had higher levels of plasma pTau at baseline (figure 3).ConclusionTau deposition in later Braak regions is associated with a higher amyloid load and increased values of pTau181, pTau217 and pTau231 at baseline in individuals in early Braak stages that accumulate tau at a more rapid rate.

Tracing the spatial extent of cortical tau over time in Alzheimer’s disease

AbstractBackgroundNeuropathological studies defined the paradigm that tau—the pathological hallmark of Alzheimer’s disease (AD)—spreads homogenously across individuals from the medial temporal lobe to the neocortex. This staging system is referred to as Braak stages. However, neuroimaging studies have since highlighted significant inter‐regional and inter‐individual differences in tau spreading patterns. We investigated the spatial extent of cortical tau over time in the amnestic AD spectrum.MethodWe included 195 amyloid‐positive ADNI participants that had at least two tau‐PET scans (90 cognitively unimpaired [CU], 66 with mild cognitive impairment [MCI], 39 with AD dementia; average follow‐up 2.6 years). We derived regional thresholds of tau positivity for 64 cortical regions and the amygdalae using Gaussian mixture modeling and applied them to all tau scans. The same approach was used to obtain thresholds for composite regions corresponding to the Braak stages. For each region, we calculated the rate of change in the amount (i.e., standardized uptake value ratio [SUVR] change) of tau pathology and the annual change in the positivity status (i.e., spatial extent change). These rates were compared between diagnostic groups using linear mixed models.ResultAcross diagnostic groups, change in tau positivity followed Braak staging; over 90% of participants positive at follow‐up either progressed or were already positive on a previous Braak stage at baseline (Fig‐1AI) and greater SUVR change was observed in temporal regions (Fig‐1B). However, across the brain, there was heterogeneity between individual patterns of tau positivity progression (Fig‐1AII). This heterogeneity was most striking in MCI patients, where many regions progressed from low to high levels of tau (Fig‐1C). Regional SUVR change did not differ between participants with AD or with MCI (Fig‐2A), but participants with MCI showed the fastest change in regional positivity compared to participants with AD and CU participants. (Fig‐2B)ConclusionWhile tau propagation follows Braak staging, inter‐individual differences can be found by considering a fine‐grained approach of regional progression to positivity. Furthermore, participants with MCI have the highest number of regions becoming abnormal annually. Our research pushes the importance of considering the entire brain when studying change in tau pathology, particularly before AD diagnosis.

Subjective language difficulties are associated with tau and objective verbal memory in older women with increased AD risk

AbstractBackgroundEarly cognitive changes in preclinical Alzheimer’s Disease (AD) include memory problems and language difficulties. Subjective cognitive complaints (SCC) are an AD risk factor and are associated with AD pathologies. Women have higher tau levels over men, despite demonstrating a life‐long “verbal memory advantage.” Therefore, SCC may be a stronger indicator of early tau accumulation than objective cognitive changes. Here, we examined the relationships among tau, subjective cognitive function, and objective cognitive function in older women at higher AD risk.Method16 older women (age: 72.3±3.1years) participated in Women Inflammation and Tau Study (WITS). The inclusion criteria are: 65+ years old, AD polygenic hazard score >50th percentile, and a telephone Montreal Cognitive Assessment score suggestive of mild cognitive impairment (MCI; range 16‐20). Tau was measured with cerebrospinal fluid (CSF) ptau181 and 18F‐MK6240 positron emission tomography (PET) with standardized uptake value ratio (SUVR) calculated in Braak1, correlating with MCI stage. Objective memory and language performance were assessed with the Rey Auditory Verbal Learning Test (RAVLT; immediate and delayed recall) and the Multilingual Naming Test (MINT), respectively. Subjective cognition was measured approximately one year later with the self‐reported Everyday Cognition Scale (ECog) memory and language subscales (higher score indicate more complaints). Spearman partial correlations analyzed the associations among tau, objective cognition, and subjective cognition while controlling for age.ResultGreater CSF ptau181 was significantly associated with higher ECog‐Language (rho = 0.62, p = 0.02), higher ECog‐Memory (rho = 0.53, p = 0.51), and lower RAVLT immediate recall (rho = ‐0.54, p = 0.046; Figure 1). More tau in Braak1 was associated with lower RAVLT immediate recall (rho = ‐0.58, p = 0.03) and higher ECog‐Language (rho = 0.45, p = 0.09), but not ECog‐Memory (p = 0.26; Figure 2). Higher ECog‐Language was significantly associated with lower RAVLT immediate (rho = ‐0.59, p = 0.02) and delayed recall (rho = ‐0.69, p<0.01; Figure 3). MINT correct responses were not related to tau and ECog (p’s>0.28).ConclusionOur preliminary results suggest that, in older women with elevated AD risk, language concerns with memory features (e.g., word finding and forgetting object names) may track with early increases in CSF ptau181 and entorhinal cortex tau‐PET. Self‐reported language decline may be predictive of tau accumulation and worsening objective verbal memory, which could be clinically important for older women.

Examining the interplay between AD pathology and intracellular/extracellular properties of cortical tissue in preclinical AD

AbstractBackgroundAD pathology affects neuronal microstructural decades before clinical manifestation of the disease. Amyloid plaques and tau tangles are key contributors to alterations in brain microstructural properties such as neurite morphology and axonal transport and packing, among others. It takes many years for these microstructural changes to build up and be reliably detected using volumetric MRI measures of neurodegeneration. Here, we examined the utility of neurite imaging – a biologically inspired model for examining cortical microstructure – to examine the impact of amyloid and tau pathology on intra‐ and extra‐cellular properties of cortical tissue and to further improve our mechanistic understanding of AD development.MethodWe utilized multimodal imaging data collected as part of ADNI‐3 including structural, multi‐shell diffusion MRI, and amyloid (18F‐florbetapir) and tau (18F‐flortaucipir) PET. The sample included 90 cognitively normal older adults (CN:23/67 amyloid‐positive/negative, age = 72.0(8.8) years) and 65 older adults with mild cognitive impairment (MCI: 36/29 amyloid‐positive/negative, 73.3(7.2) years). Neurite orientation dispersion and density imaging (NODDI) measures including intracellular volume fraction (ICVF), neurite orientation and dispersion index (ODI) in gray matter, standardized uptake value ratio (SUVR) for amyloid/tau PET and cortical thickness were extracted for 360 regions defined by surface‐based HCP atlas. We performed mediation analyses to examine the interplay between AD pathology and intracellular/extracellular properties of brain tissue and also compared the clinical utility of cortical neurite measures against volumetric MRI in detecting brain changes associated with AD pathology (tau burden) in preclinical AD.ResultMediation analyses showed that tau burden mediates the impact of amyloid on intracellular properties of brain tissue (ICVF) in medial and lateral temporal structures (Fig.1A) whereas ODI is a significant mediator of the effect of extracellular amyloid accumulation on intra‐cellular tau burden in entorhinal cortex (Fig.1B) in amyloid‐positive older adults. Further, among the regions with highest tau burden in amyloid‐positive CN group, ICVF changes in lateral temporal cortex successfully distinguished preclinical AD from amyloid‐negative CN and was associated with tau pathology.ConclusionOverall, these preliminary results suggest that accumulation of amyloid plaques results in reduction of neurite complexity while build‐up of tau reduces the intracellular volume fraction in preclinical stage of AD.

Evaluation of the association between circulatory markers of neuroinflammation and Alzheimer’s disease pathology

AbstractBackgroundIncreasing evidence suggests that neuroinflammation and astrogliosis have a prominent role in the spread of pathology and the development of cognitive impairment in Alzheimer’s disease (AD). Circulating plasma markers of neuroinflammation, such as the glial fibrillary acid protein (GFAP), have recently become available, and early observations suggest a robust association with brain pathology. Positron emission tomography (PET) is a molecular imaging technique that allows visualisation and quantification of AD pathology in vivo. The aim of this study was to evaluate the association between GFAP and AD pathology, and its interaction with cognitive decline.Method121 subjects from the Geneva Memory Centre underwent amyloid and tau PET, blood collection, and mini‐mental state examination (MMSE). Amyloid uptake was calculated as centiloid whereas tau was quantified as standardised uptake value ratio. Association of centiloid and tau with GFAP was assessed using a multivariate linear regression model, corrected for age, gender, and MMSE. Mediation analysis described the mediating effect of GFAP on the association between centiloid and tau. Ninety‐four subjects had a follow‐up MMSE after at least 12 months. Linear regression was used to assess the effect of GFAP on the annual rate of change of MMSE (corrected for centiloid, global tau, age, and gender). Mediation analysis was used to test whether the relationship between rate of MMSE change and tau could be explained by a mediation of GFAP.ResultThe mean (SD) age of the participants was 72.6 (7.6) years, and 61 of 121 subjects were men. GFAP was significantly associated with increased tau, but not with centiloid. GFAP partially mediated the effect of centiloid on global tau (mediated proportion = 14%, p = 0.03). The rate of MMSE change was significantly associated with GFAP, and global tau, but not with centiloid. Moreover, GFAP partially mediated the effect between global tau SUVR and change of MMSE scores (52%, p<0.01).ConclusionElevated GFAP is associated with tau. GFAP also partially explains the effect of amyloid pathology on tau accumulation and of tau pathology on subsequent cognitive decline. These results support neuroinflammation and astrogliosis as a relevant contributor to AD pathology, which can be monitored in blood.