Lowe, Val J.

Abstract INTRODUCTION We examined when Alzheimer's disease biomarkers become informative by identifying age‐related breakpoints with slope‐changing trajectories. METHODS In 2082 Mayo Clinic Study of Aging participants, we modeled plasma amyloid beta (Aβ)42/40, phosphorylated tau (p‐tau)181, glial fibrillary acidic protein (GFAP), neurofilament light chain (NfL), amyloid/tau positron emission tomography (PET), hippocampal volume (HVa), and global cognition. Generalized additive models described age trends; Davies' test and piecewise linear regression estimated breakpoints. A C2N subsample ( n = 462) provided mass‐spectrometry plasma markers (p‐tau181, p‐tau217, their ratios, Aβ42/40). RESULTS In the full cohort, Aβ42/40, HVa, and cognition declined with age; p‐tau181, NfL, GFAP, and amyloid/tau PET increased. We observed single breakpoints (years, 95% CI): GFAP 68.1 (63.5–71.8), NfL 70.7 (65.9–75.6), p‐tau181 67.2 (60.3–70.3), amyloid PET 62.3 (56.2–69.3), HVa 68.1 (63.1–71.9), cognition 59.8 (55.4–66.0); tau PET showed none. In the mass‐spectrometry subset, p‐tau217 and p‐tau181 broke at 72.6; their ratios and Aβ42/40 showed no breakpoints. DISCUSSION Breakpoints cluster near late midlife, suggesting windows for screening and monitoring.

Background TAR DNA-binding protein 43 (TDP-43) proteinopathy contributes to Alzheimer's disease progression, but diagnosis remains autopsy-dependent. Objective This study aimed to develop a predictive model using FDG-PET imaging to identify brain regions associated with TDP-43 pathology in vivo. Methods Penalized logistic regression analyzed data from 294 participants and a subset of 159 with Braak and Thal ≥4. Features included FDG standard uptake value ratios (SUVRs) from 123 brain regions and age. Participants were split into training (90%) and testing (10%) datasets, with significant predictors identified by non-zero coefficients at optimal lambda. Results The model achieved 68% accuracy (AUC = 0.70) in 294 participants, highlighting the middle temporal gyrus, parahippocampal gyrus, and hippocampus. In the subset (n = 159), accuracy was 65% (AUC = 0.71), with the medial amygdala and precentral gyrus as key predictors of TDP-43 pathology. Conclusions This study suggests a moderate predictive accuracy of FDG-PET to identify brain regions associated with Alzheimer's disease-related TDP-43 proteinopathy.

Abstract INTRODUCTION The tau positron emission tomography (PET) overlap index (OI) has shown promise in maximizing signal‐to‐noise for longitudinal tau PET imaging, particularly for early tau pathology, but requires validation against neuropathology. METHODS Fifty‐seven participants who underwent serial tau PET imaging (flortaucipir) and subsequent autopsy were included. Tau PET OI and standardized uptake value ratios (SUVRs) were compared across neuropathological diagnoses. RESULTS Tau PET OI showed greater concordance with neurofibrillary tangle (NFT) severity in the entorhinal cortex (a key region for Alzheimer's disease [AD] tauopathy) than SUVR, particularly in early Braak tangle stages (positivity: 52.2% for OI vs. 13.0% for SUVR). OI detected overlapping tau voxels that exhibited spatial correspondence with immunohistochemical and autoradiography measures of tau deposition across both AD and non‐AD tauopathies. DISCUSSION These findings demonstrate the enhanced capacity of OI in serial tau PET to robustly detect early and spatially localized tau pathology, supporting its application as a sensitive imaging metric in AD and select non‐AD tauopathies.

Abstract INTRODUCTION Globular glial tauopathy (GGT) is a rare type of frontotemporal lobar degeneration (FTLD) characterized by deposition of 4‐repeat tau. Detecting GGT with tau positron emission tomography (tau‐PET) is challenging. We aim to determine the associations between tau‐PET, autoradiography, and neuropathology methods in GGT. METHODS We identified three patients with GGT who had completed antemortem tau‐PET. Healthy control and two patients with Alzheimer's disease (AD) were also included for comparison. We analyzed gray matter (GM) and white matter (WM) from the superior/middle frontal gyrus (S/M‐FG) and the superior/middle temporal gyrus (S/M‐TG). Immunohistochemical staining was performed with antibodies against phospho‐tau (AT8, PHF‐1, RD4), glial fibrillary acidic protein (GFAP), and resting microglia (ionized calcium‐binding adaptor molecule 1; Iba1). Immunofluorescence with a fluorescent tau‐PET analog (T726) was performed. Regional tau‐PET standardized uptake value ratios (SUVRs) were calculated for comparative GM and WM regions. Autoradiographic studies with 18F‐AV1451 were also conducted. RESULTS Tau‐PET showed increased uptake in the WM regions of the S/M‐FG and S/M‐TG in GGT, and the GM regions in AD. Co‐localization was observed between T726 and PHF‐1, RD4, and GFAP in the WM in the patients with GGT, whereas co‐localization was observed with PHF‐1 predominantly in the GM in AD. Little co‐localization was observed with Iba1. In vitro 18F‐AV1451 autoradiography studies demonstrated minimal binding in GGT. Tau‐PET differentiated underlying GGT from AD based on the relative involvement of the WM and GM. CONCLUSION Histopathologic findings suggest that some flortaucipir uptake in GGT may represent underlying 4R tau, whereas autoradiographic analysis suggests that uptake is likely due to off‐target binding. Further studies with larger cohorts are needed to determine the pathological basis of flortaucipir uptake in GGT.

Importance Sex differences are increasingly recognized as modifiers of Alzheimer disease and related dementias, with women exhibiting greater tau burden and faster cognitive decline than men. Even though α-synuclein copathology frequently occurs in Alzheimer disease, its contribution to sex differences in disease progression is unclear. Objective To test whether α-synuclein positivity, measured using cerebrospinal fluid seed amplification assay (SAA), is differentially associated with tau accumulation in women vs men across the Alzheimer disease continuum. Design, Setting, and Participants This cohort study used longitudinal tau positron emission tomography from the Alzheimer’s Disease Neuroimaging Initiative collected between 2015 and 2023, with a median (IQR) follow-up of 1.23 (0.00-3.84) years. Participants were stratified by cerebrospinal fluid α-synuclein seed amplification assay status and sex. Participants were cognitively unimpaired or cognitively impaired (mild cognitive impairment or dementia) at baseline. Exposure Cerebrospinal fluid α-synuclein status determined by SAA and dichotomized as SAA negative or SAA positive. Main Outcomes and Measures Tau burden was quantified as standardized uptake value ratio (SUVr) in the medial temporal composite region of interest. Linear mixed-effects models tested SAA by sex by time interactions on longitudinal tau accumulation, adjusting for baseline age, baseline cognitive status, apolipoprotein E ε4 carrier status, and site. Sample size estimates were calculated to detect 25% and 50% treatment effects with 80% power in those with cognitive impairment. Results Among 415 participants (mean [SD] age, 72.3 [7.6] years; 220 women [53%]; 69 SAA positive [17%] and 346 SAA negative [83%]), there was a significant interaction between SAA status, sex, and time on tau accumulation (β, 0.061; 95% CI, 0.030-0.093; P < .001). Women with positive SAA results exhibited the fastest tau accumulation compared with other groups (0.066 SUVr per year; 95% CI, 0.043 to 0.089 SUVr per year; P < .001). Clinical trials targeting tau pathology in cognitively impaired individuals with 18-month follow-up would require 129 SAA-positive women to detect a 25% treatment effect with 80% power, compared with 518 SAA-negative women. Conclusions and Relevance In this cohort study of participants across the Alzheimer disease continuum, α-synuclein copathology was associated with faster tau accumulation in women than men. These findings may inform sex-specific interpretation of α-synuclein biomarkers and trial design.

Abstract Associations of Alzheimer’s disease biomarker progression with cognitive decline are important to inform patient prognosis. Of particular interest is how newly available plasma biomarkers evolve relative to cognitive decline. The goals of this work are to measure how much earlier versus later an individual’s progression on plasma and PET Alzheimer’s disease biomarkers is associated with earlier versus later cognitive progression and to estimate the average timeline of progression of these processes in the population. In this cohort study of 2369 Mayo Clinic Study of Aging (MCSA) and 1591 Alzheimer’s Disease Neuroimaging Initiative (ADNI) participants, we fit non-linear mixed-effects models to estimate how much earlier versus later each individual progresses on plasma phosphorylated tau (p-tau)217, amyloid PET, tau PET and auditory verbal learning test (AVLT) sum of trials relative to the population mean (individual adjustment), the associations of these individual adjustments among biomarker pairs and how covariates affect the timing of biomarker progression. The association of individual adjustments implies mechanistic associations and the amount of variability in cognitive decline accounted for by each biomarker. By applying cut-off points, we also estimated the relative timing that these biomarkers become abnormal in the population. Associations of individual adjustments were moderate between all biomarkers and AVLT (R = 0.38–0.47) in the MCSA and stronger (R = 0.74–0.81) in ADNI; plasma p-tau217 accounted for 16% of the variability in timing of AVLT decline in the MCSA and 64% in ADNI. APOE ɛ4 carriership was associated with earlier biomarker progression. AVLT became abnormal after the biomarkers up to age 90, after which AVLT was estimated to become abnormal prior to tau biomarkers. The association of the timing of plasma and PET Alzheimer’s disease biomarker progression with cognitive decline was modest in the MCSA population-based sample and stronger in the Alzheimer’s disease-enriched ADNI cohort. The timing of plasma p-tau217 progression explained a similar degree of variability in AVLT progression as amyloid PET, supporting its utility as a marker of disease progression. The estimated temporal ordering of biomarkers and cognitive abnormality was as anticipated (amyloid, tau, cognition) up to the age of 90, beyond which AVLT was estimated to become abnormal prior to tau biomarkers, likely related to the effects of non-Alzheimer’s disease co-pathologies.

Abstract Distinguishing atypical parkinsonian disorders (APS) from Parkinson’s disease (PD) remains challenging due to overlapping clinical features, yet accurate differentiation is critical for prognosis and treatment. Here, we employed multi-model diffusion MRI (dMRI) analysis to characterize microstructural alterations across corticobasal syndrome (CBS), progressive supranuclear palsy-Richardson syndrome (PSP-RS) and PD, with the aim of identifying which dMRI model provides optimum differentiation. We analyzed 25 CBS, 42 PSP-RS, and 21 PD participants compared to 35 age and sex-matched controls. Using a clinically feasible 3-shell high angular resolution diffusion imaging (HARDI) protocol, we applied 11 metrics from five complementary dMRI models—diffusion tensor imaging (DTI), free-water-eliminated model of DTI (FWE), neurite orientation dispersion and density imaging (NODDI), tissue-weighted NODDI, and Fixel Density (FD) in fixel-based analysis (FBA) —to comprehensively assess regional white and gray matter integrity. Group differentiation was assessed using Cohen’s d effect sizes and spearman correlations were assessed between dMRI metrics and clinical scales. Distinct microstructural signatures were observed across disorders and the sensitivity of the dMRI models differed. In group contrasts, DTI and NODDI-derived metrics consistently captured the strongest effects in midbrain and peduncular pathways for PSP-RS, whereas precentral and corticospinal alterations in CBS were most prominent using NODDI and FBA measures. Free-water-corrected metrics showed attenuated group differences. Across clinical-diffusion analyses, NODDI metrics exhibited the most robust associations with disease severity, while DTI and FWE measures detected more limited, regionally constrained effects. Together, these findings highlight complementary yet distinct sensitivities of tensor, free-water, multi-compartment, and fixel-based models to APS-related neurodegeneration.

Abstract Background Neuroinflammation plays a crucial role in neuronal damage, synaptic dysfunction, and impaired neurogenesis, significantly contributing to Alzheimer's Disease (AD) progression. To address this, we assessed ER176's effectiveness in detecting neuroinflammation in cognitively unimpaired (CU) A–, CU A+, mild cognitive impairment (MCI), and AD participants, with a particular focus on their amyloid and tau status. This research aims to help identify suitable candidates for specialized treatment when adversely impacted by neuroinflammation. Method Participants from the Mayo Clinic Study of Aging were recruited for this study. The study included four participant groups: CU A– ( n = 25), CU A+ ( n = 25), MCI A+ ( n = 25), and AD ( n = 15). We explored the variations in neuroinflammation PET results among different groups. Result When compared to CU A–, both CU A+ and MCI A+ groups (Figure 1) showed greater regional neuroinflammation. AD exhibited more widely affected regions with neuroinflammation (temporal, occipital, and parietal lobes) than CU A‐ over the PVC spectrum (Figure 1). Minimally more neuroinflammation was seen (temporal lobes) in MCI A+ than CU A+ (Figure 1). AD had more widespread regional neuroinflammation vs CU A+ (Figure 1) than in MCI A+ vs CU+. The least difference in neuroinflammation is seen in MCI A+ vs AD (Figure 1). For A+ vs A‐, A+ showed more widespread neuroinflammation (Figure 2). T+ (tau>=1.29) vs T‐ (tau<1.29) showed more neuro inflammation with T+ (Figure 2). Comparisons varied modestly in significance level with PVC method (Figures 1 and 2). Conclusion The findings demonstrate that neuroinflammatory changes are associated with AD pathology. Even at early stages, neuroinflammation is associated with CU+. As the condition progresses, neuroinflammation extends to more brain regions and is associated with increased A+ and T+ pathology in MCI A+ and AD. These results suggest an early and persistent role of neuroinflammation in the progression AD pathology, indicating that therapy options could include early anti‐inflammatory intervention, even prior to clinical symptoms, along with treatment during clinical manifestations. PVC methods used may provide somewhat variable results.

Abstract Background Tau‐PET tracers are essential for visualizing pathology in Alzheimer's (AD). High detectability to tau is crucial for early detection and monitoring of tau deposition. This study compares the noise to dynamic range ratio (NRR) of [ 18 F]FTP, [ 18 F]MK6240, [ 18 F]PI2620, and [ 18 F]RO948, cross‐sectionally and longitudinally. Methods 460 individuals from the HEAD study (23 cognitively unimpaired (CU) young, 249 CU old and 188 cognitively impaired) underwent [ 18 F]FTP and [ 18 F]MK6240 tau‐PET scans; 94 additionally received [ 18 F]PI2620 and [ 18 F]RO948. A subset of 28 individuals (15 CU and 13 CI) underwent [ 18 F]FTP and [ 18 F]MK6240 follow‐up scans (1.5 ± 0.1 years later). Annual change was measured as [(followup‐baseline)/time between scans]. Noise was calculated as the standard deviation (SD) of CU Aβ‐ participants aged ≤65 (SD CUAβ‐≤65 ). The dynamic range was calculated as the SD across all subjects (SD range ). A lower the NRR (=SD CUAβ‐≤65 /SD range ) indicates more detectability. Analyses were performed at both region‐of‐interest and voxel‐wise levels. Results Across the whole cohort, [ 18 F]MK6240 exhibited lower NRR than [ 18 F]FTP in all regions. Voxel‐wise, differences were most pronounced in the frontal medial temporal regions (Figure 1). Within the four‐tracers subset, [ 18 F]PI2620 and [ 18 F]FTP showed the highest NRR in Braak II, followed by [ 18 F]RO948 and [ 18 F]MK6240. In Braak IV‐VI, [ 18 F]MK6240 consistently demonstrated the lowest values, followed by [ 18 F]PI2620, [ 18 F]FTP and [ 18 F]RO948. Similarly, in metatemporal‐ROI and Braak III, [ 18 F]MK6240 remained the lowest, however followed by [ 18 F]FTP, [ 18 F]PI2620 and [ 18 F]RO948 (Figure 2). Lower [ 18 F]MK6240 NRR was due to larger SD range , while [ 18 F]FTP's lower values stemmed from smaller SD CUAβ‐≤65 . Conversely, high [ 18 F]PI2620 and [ 18 F]RO948 values are driven by larger SD CUAβ‐≤65 . Longitudinal analyses further confirmed that [ 18 F]MK6240 exhibited the lowest NRR across the entire brain, including AD‐related regions, with voxel‐wise differences mainly in the temporal and parietal lobes. Conclusion Tau‐PET tracers exhibit significant variability in detectability. [ 18 F]MK6240 consistently demonstrated lower NRR, implying better detectability across all regions, cross‐sectionally and longitudinally. Despite differences in NRR, [ 18 F]FTP, [ 18 F]RO948 and [ 18 F]PI2620 followed similar pattern. These results provide insights into the differential tracer detectability, helping guide their optimal use in detecting and tracking tau pathology. Ongoing follow‐up scans will further clarify longitudinal tracer detectability and its implications for tau progression in AD.