Standardized Uptake Value Ratio Research Articles

Subjective cognitive impairment score associate with regional amyloid burden and brain atrophy in subjective cognitive decline subjects

AbstractBackgroundSubjective cognitive decline (SCD) is now regarded as the first preclinical stage of Alzheimer’s disease (AD) spectrum disorders. It is important to predict which patients would progress to dementia, and screening tools might be helpful. In this study, we aimed to investigate the possible correlations between AD biomarkers‐regional amyloid burden and volume changes‐and Korean Dementia Screening Questionnaire‐Cognition (KDSQ‐C) score in SCD.MethodThis study analyzed SCD data from prospective population cohort study from July 2018 to December 2020. Brain magnetic resonance imaging (MRI) volumetry, visual and standardized uptake value ratio (SUVR) analysis of 18F‐Florbetaben brain amyloid Positron Emission Tomography (PET) were performed. Demographics, physical data, social and physiological functions were also obtained.KDSQ‐C was administered to SCD subjects as part of the clinical evaluation at the 36 month follow‐up visit. KDSQ‐C included 15 questions that assess 3 dimensions: memory impairment (items 1‐5), other cognitive impairments including language impairments (items 6‐10), and the ability to perform complex tasks in daily life (items 11‐15).ResultPrevalence of subjective cognitive impairment (KDSQ‐C ≧6) among 86 subjects was 73.3%.. No significant difference was observed between groups in terms of demographic characteristics including age, sex and APOE Ɛ4 status and neuropsychological test. However, regional SUVR (amygdala, inferior temporal gyrus and precuneus) and global SUVR were significantly higher in subjectively cognitive impaired group(p<0.05). There were no brain volume differences between groups.For volumetry and KDSQ‐C correlation analysis, partial correlation analysis controlled for age, sex and APOE Ɛ4 status showed significant negative correlation between left entorhinal cortex, right hippocampal volume and KDSQ‐C (r = ‐0.230, p = 0.046; r = ‐0.226, p = 0.049). Similar association was also found between KDSQ‐C memory domain score and brain volume.ConclusionKDSQ‐C can be a useful tool for screening SCD patients at a higher risk with higher amyloid deposition and brain atrophy.This study was supported by a grant from the Ministry of Health and Welfare, HI18C0530

Amyloid and tau deposition is associated with performance on tests of auditory processing in the brain

AbstractBackgroundAlzheimer’s disease pathophysiology may affect sound processing (central auditory function) in the brain. This study aims to investigate the link between tests of central auditory function, such as dichotic digits, and brain pathology in older adults at high risk for developing dementia.Method28 individuals (13 cognitively unimpaired (CU) and 15 mild cognitively impaired (MCI)) were enrolled (Table 1). Amyloid deposition was assessed with [18F] AZD4694 PET and tau accumulation was assessed with [18F]MK6240 PET. Standard uptake value ratios (SUVR) were determined using the cerebellar and the inferior cerebellar cortex as reference region for amyloid and tau PET, respectively. Hearing assessments were conducted using a custom audiological testing system from Creare LLC. Voxel‐based regression models evaluated the association between dichotic digit scores and amyloid and tau deposition as assessed by PET, adjusting for Pure Tone Average (PTA) and a control condition for speech in noise (Triple digits score). Random field theory (RFT) was used to correct for multiple comparisons.ResultIn the voxel‐wise analysis, negative associations between dichotic digits scores and amyloid‐PET were found in the temporal, occipital and parietal areas. Negative associations between dichotic digits scores and tau‐PET were present in the temporal area, with higher t‐values in the primary and secondary somatosensory cortices (Figure 1, panel A). Negative correlations were found between dichotic digits scores and both amyloid (p<0.001) and tau (p<0.05) SUVRs (Figure 1, panel B). In addition, dichotic digits scores were significantly lower in MCI individuals (p<0.001) (Figure 1, panel C).ConclusionThis study is the first to assess associations between central auditory hearing in CU and MCI individuals using PET biomarkers. These findings highlight the link between central auditory deficits and AD hallmarks in auditory processing‐related brain regions. This suggests a potential decreased capacity for interhemispheric transfer in mildly cognitively impaired individuals.

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, APOEe4 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.

Amyloid and tau deposition is associated with performance on tests of auditory processing in the brain

AbstractBackgroundAlzheimer’s disease pathophysiology may affect sound processing (central auditory function) in the brain. This study aims to investigate the link between tests of central auditory function, such as dichotic digits, and brain pathology in older adults at high risk for developing dementia.Method28 individuals (13 cognitively unimpaired (CU) and 15 mild cognitively impaired (MCI)) were enrolled (Table 1). Amyloid deposition was assessed with [18F] AZD4694 PET and tau accumulation was assessed with [18F]MK6240 PET. Standard uptake value ratios (SUVR) were determined using the cerebellar and the inferior cerebellar cortex as reference region for amyloid and tau PET, respectively. Hearing assessments were conducted using a custom audiological testing system from Creare LLC. Voxel‐based regression models evaluated the association between dichotic digit scores and amyloid and tau deposition as assessed by PET, adjusting for Pure Tone Average (PTA) and a control condition for speech in noise (Triple digits score). Random field theory (RFT) was used to correct for multiple comparisons.ResultIn the voxel‐wise analysis, negative associations between dichotic digits scores and amyloid‐PET were found in the temporal, occipital and parietal areas. Negative associations between dichotic digits scores and tau‐PET were present in the temporal area, with higher t‐values in the primary and secondary somatosensory cortices (Figure 1, panel A). Negative correlations were found between dichotic digits scores and both amyloid (p<0.001) and tau (p<0.05) SUVRs (Figure 1, panel B). In addition, dichotic digits scores were significantly lower in MCI individuals (p<0.001) (Figure 1, panel C).ConclusionThis study is the first to assess associations between central auditory hearing in CU and MCI individuals using PET biomarkers. These findings highlight the link between central auditory deficits and AD hallmarks in auditory processing‐related brain regions. This suggests a potential decreased capacity for interhemispheric transfer in mildly cognitively impaired individuals.

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.

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.

Comparison of self‐similarity measures in FDG‐PET images and association with disease progression risk

AbstractBackgroundDecreased image self‐similarity of repeated FDG‐PET scans has been suggested to indicate increased risk for disease progression. Here, we compared several self‐similarity measures based on conventionally used voxel‐ and ROI‐based approaches and those based on patterns of cortical metabolism.MethodFrom the MCSA/ADRC, we included 376 cognitively unimpaired (CU) individuals and those with a clinical diagnosis of MCI (n = 55) or AD (n = 20) who had two FDG‐PET images within 2‐3 years and clinical follow‐up available. We compared image self‐similarity for three approaches: voxel, ROI and “eigenbrain” (Fig.1). For the voxel approach, FDG‐PET images were normalized to template space, grey matter masked, and intensity normalized to the pons to create standard uptake value ratios (SUVR) for each voxel. From these images, mean SUVR were extracted for 122 ROIs (MCALT‐ADIR122) for the ROI approach. For the “eigenbrain” approach, the SUVR images were transformed to a latent space embedding composed of 253 components (“eigenbrains”) and reflecting metabolism patterns, that was generated in an independent sample of 7008 FDG‐PET images. For each approach, image self‐similarity between baseline and follow‐up values (voxel, ROI or eigenbrain) was determined using three metrics (Pearson correlation, cosine, Euclidean distance). We computed AUC to determine which approach and metric would best discriminate between groups. We used Cox regression analyses to assess whether the metrics could predict disease progression.ResultComparing each distance metric across approaches, AUC was highest in differentiating clinical diagnoses using self‐similarity measures based on eigenbrains, then voxels, then ROIs (e.g., Euclidean distance CU vs AD AUC eigenbrain: 0.86, voxel: 0.75, ROI: 0.71; Fig.1). Across all approaches, Euclidean distance always discriminated best between classes. Eigenbrain‐based Euclidean distance was associated with risk for progression to MCI in CU (HR [95%CI]: 1.25 [1.05, 1.49]), and eigenbrain‐based cosine and Euclidean distances were associated with risk for progression to AD in MCI (1.61 [1.1, 2.34] and 1.53 [1.01, 2.31], respectively), while we found no associations for voxel‐ or ROI‐based distance measures.ConclusionEigenbrain‐based measures outperformed other, more conventional approaches in discriminating clinical diagnoses, and were associated with risk for disease progression. Our results suggest that decreased self‐similarity in metabolism patterns informs on disease stage and prognosis.

The interplay between White Matter Hyperintensities and regional β‐Amyloid on Defaults Mode Network

AbstractBackgroundCerebral small vessel ischemic disease (SVID) has been suggested to contribute to the pathogenesis of Alzheimer’s disease (AD). Yet, the mechanistic role of SVID in potentially contributing to AD pathology is unclear. The main objective of this study was to test the hypothesis that axonal SVID influences amyloid β (Aβ) levels within connected default mode network (DMN) tracts and cortical regions in cognitively unimpaired older adults.MethodRegional Standard Uptake Value ratios (SUVr) from Aβ‐PET, and white matter hyperintensity (WMH) volumes from 3D MRI FLAIR images were analyzed across a sample of 72 clinically‐unimpaired (Mini‐Mental State Examination (MMSE) ≥ 26), aged participants from the Alzheimer’s Disease Neuroimaging Initiative (ADNI3). The association of WMH volumes in major fiber tracts projecting from cortical DMN regions and Aβ‐PET SUVr in the connected cortical DMN regions were analyzed using linear regression models adjusted for age, sex, ApoE and total brain volumes.ResultThe regression analyses demonstrate that increased WMH volumes in the superior longitudinal fasciculus (SLF) was associated with increased regional SUVr in the inferior parietal lobule (IPL) (p = 0.011).ConclusionThe findings suggest that the relation between Aβ parietal cortex is partially driven by SVID in downstream axonal pathways in pAD. The biological relationships and interplay between Aβ and white matter microstructure alterations that precede overt WMH development across the continuum of AD progression warrants further study.

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 ß‐amyloid (Aß) 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 Aß‐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.ResultBaseline 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.ConclusionThe 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.

Generative deep learning model‐based manifold construction for ATN biomarkers

AbstractBackgroundGenerative models have the potential to be beneficial in neuroimaging, as they can produce new data samples that closely resemble the ones they were trained on. This can assist in addressing the scarcity of brain scan data, which is a significant issue in neuroscience.MethodIn this study, we developed a one‐ring convolution‐based generative adversarial network (GAN) to generate ATN biomarkers, which operate on an icosahedron cortical mesh structure on a cortical surface. Data from the Alzheimer’s Disease Neuroimaging Initiative cohort was used in the study, including AV45, AV1451, and T1 magnetic resonance imaging (MRI) scans from 2283 subjects. The cortical thickness of all T1 MRI images was calculated using a Freesurfer pipeline and resampled into icosahedron subdivision level 3. AV45 and AV1451 scans were then converted into standard uptake value ratio (SUVR) and mapped to the cortical surface before being resampled into icosahedron subdivision level 3. For each modality, the proposed GAN was trained and evaluated using density and coverage metrics, which measure the fidelity and diversity of generated samples. Also, we validated the efficacy of the constructed ATN manifolds using the data augmentation scenario. Specifically, we evaluated the performance of tau stage classifiers using cortical thickness data with and without augmenting tau PET data from our manifolds.ResultOur proposed GAN achieved high performance in density and coverage. Specifically, the density and coverage for the amyloid SUVR were 1.0 and 0.97, for the tau SUVR were 1.34 and 1.0, and for the cortical thickness were 1.66 and 0.98, respectively, showing high performance in generating realistic and diverse samples for all modalities. The effectiveness of our proposed GAN was further demonstrated to show improved performance in the Tau Braak stage classification experiment when using the generated data. When augmented with generated data, the classification accuracy was improved from 0.77 to 0.84 in terms of AUC scores.ConclusionOur proposed GAN achieved high performance in density and coverage, generating realistic and diverse samples for each ATN biomarker, and demonstrated improved performance in a Tau Braak stage classification experiment when using the generated data.

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.

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.

Clinical Manifestations.

Neurodegenerative 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. We 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. 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. Our 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.

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.

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.