Jack, Clifford R.

AbstractINTRODUCTIONAge‐related and Alzheimer's disease (AD) dementia–related neurodegeneration impact brain health. While morphometric measures from T1‐weighted scans are established biomarkers, they may be less sensitive to earlier changes. Neurite orientation dispersion and density imaging (NODDI), offering biologically meaningful interpretation of tissue microstructure, may be an advanced brain health biomarker.METHODSWe contrasted regional gray matter NODDI and morphometric evaluations concerning their correlation with (1) age, (2) clinical diagnosis stage, and (3) tau pathology as assessed by AV1451 positron emission tomography.RESULTSOur study hypothesizes that NODDI measures are more sensitive to aging and early AD changes than morphometric measures. One NODDI output, free water fraction (FWF), showed higher sensitivity to age‐related changes, generally better effect sizes in separating mild cognitively impaired from cognitively unimpaired participants, and stronger associations with regional tau deposition than morphometric measures.DISCUSSIONThese findings underscore NODDI's utility in capturing early neurodegenerative changes and enhancing our understanding of aging and AD.Highlights Neurite orientation dispersion and density imaging can serve as an effective brain health biomarker for aging and early Alzheimer's disease (AD). Free water fraction has higher sensitivity to normal brain aging. Free water fraction has stronger associations with early AD and regional tau deposition.

[ 18 F]-Flortaucipir positron emission tomography (PET) is considered a good biomarker of Alzheimer’s disease. However, it is unknown how flortaucipir is associated with the distribution of tau across brain regions and how these associations are influenced by amyloid-β. It is also unclear whether flortaucipir can detect tau in definite primary age–related tauopathy (PART). We identified 248 individuals at Mayo Clinic who had undergone [ 18 F]-flortaucipir PET during life, had died, and had undergone an autopsy, 239 cases of which also had amyloid-β PET. We assessed nonlinear relationships between flortaucipir uptake in nine medial temporal and cortical regions, Braak tau stage, and Thal amyloid-β phase using generalized additive models. We found that flortaucipir uptake was greater with increasing tau stage in all regions. Increased uptake at low tau stages in medial temporal regions was only observed in cases with a high amyloid-β phase. Flortaucipir uptake linearly increased with the amyloid-β phase in medial temporal and cortical regions. The highest flortaucipir uptake occurred with high Alzheimer’s disease neuropathologic change (ADNC) scores, followed by low-intermediate ADNC scores, then PART, with the entorhinal cortex providing the best differentiation between groups. Flortaucipir PET had limited ability to detect PART, and imaging-defined PART did not correspond with pathologically defined PART. In summary, spatial patterns of flortaucipir mirrored the histopathological tau distribution, were influenced by the amyloid-β phase, and were useful for distinguishing different ADNC scores and PART.

Abstract INTRODUCTION Tau‐positron emission tomography (PET) outcome data of patients with Alzheimer's disease (AD) cannot currently be meaningfully compared or combined when different tracers are used due to differences in tracer properties, instrumentation, and methods of analysis. METHODS Using head‐to‐head data from five cohorts with tau PET radiotracers designed to target tau deposition in AD, we tested a joint propagation model (JPM) to harmonize quantification (units termed “CenTauR” [CTR]). JPM is a statistical model that simultaneously models the relationships between head‐to‐head and anchor point data. JPM was compared to a linear regression approach analogous to the one used in the amyloid PET Centiloid scale. RESULTS A strong linear relationship was observed between CTR values across brain regions. Using the JPM approach, CTR estimates were similar to, but more accurate than, those derived using the linear regression approach. DISCUSSION Preliminary findings using the JPM support the development and adoption of a universal scale for tau‐PET quantification. Highlights Tested a novel joint propagation model (JPM) to harmonize quantification of tau PET. Units of common scale are termed “CenTauRs”. Tested a Centiloid‐like linear regression approach. Using five cohorts with head‐to‐head tau PET, JPM outperformed linearregressionbased approach. Strong linear relationship was observed between CenTauRs values across brain regions.

Abstract INTRODUCTION We aimed to evaluate clinical interpretation cutpoints for two plasma phosphorylated tau (p‐tau)217 assays (ALZpath and Lumipulse) as predictors of amyloid status for implementation in clinical practice. METHODS Clinical performance of plasma p‐tau217 against amyloid positron emission tomography status was evaluated in participants with mild cognitive impairment or mild dementia ( n = 427). RESULTS Using a one‐cutpoint approach (negative/positive), neither assay achieved ≥ 90% in both sensitivity and specificity. A two‐cutpoint approach yielding 92% sensitivity and 96% specificity provided the desired balance of false positives and false negatives, while categorizing 20% and 39% of results as indeterminate for the Lumipulse and ALZpath assays, respectively. DISCUSSION This study provides a systematic framework for selection of assay‐specific cutpoints for clinical use of plasma p‐tau217 for determination of amyloid status. Our findings suggest that a two‐cutpoint approach may have advantages in optimizing diagnostic accuracy while minimizing potential harm from false positive results. Highlights Phosphorylated tau (p‐tau)217 cutpoints for detection of amyloid pathology were established. A two‐cutpoint approach exhibited the best performance for clinical laboratory use. p‐tau217 assays differed in the percentage of results categorized as intermediate.

Abstract Progressive supranuclear palsy (PSP) is a neurodegenerative tauopathy that presents with highly heterogenous clinical syndromes. We perform cross-sectional data-driven discovery of independent patterns of brain atrophy and hypometabolism across the entire PSP spectrum. We then use these patterns to predict specific clinical features and to assess their relationship to phenotypic heterogeneity. We included 111 patients with PSP (60 with Richardson syndrome and 51 with cortical and subcortical variant subtypes). Ninety-one were used as the training set and 20 as a test set. The presence and severity of granular clinical variables such as postural instability, parkinsonism, apraxia and supranuclear gaze palsy were noted. Domains of akinesia, ocular motor impairment, postural instability and cognitive dysfunction as defined by the Movement Disorders Society criteria for PSP were also recorded. Non-negative matrix factorization was used on cross-sectional MRI and fluorodeoxyglucose-positron emission tomography (FDG-PET) scans. Independent models for each as well as a combined model for MRI and FDG-PET were developed and used to predict the granular clinical variables. Both MRI and FDG-PET were better at predicting presence of a symptom than severity, suggesting identification of disease state may be more robust than disease stage. FDG-PET predicted predominantly cortical abnormalities better than MRI such as ideomotor apraxia, apraxia of speech and frontal dysexecutive syndrome. MRI demonstrated prediction of cortical and more so sub-cortical abnormalities, such as parkinsonism. Distinct neuroanatomical foci were predictive in MRI- and FDG-PET-based models. For example, vertical gaze palsy was predicted by midbrain atrophy on MRI, but frontal eye field hypometabolism on FDG-PET. Findings also differed by scale or instrument used. For example, prediction of ocular motor abnormalities using the PSP Saccadic Impairment Scale was stronger than with the Movement Disorders Society Diagnostic criteria for PSP oculomotor impairment designation. Combination of MRI and FDG-PET demonstrated enhanced detection of parkinsonism and frontal syndrome presence and apraxia, cognitive impairment and bradykinesia severity. Both MRI and FDG-PET patterns were able to predict some measures in the test set; however, prediction of global cognition measured by Montreal Cognitive Assessment was the strongest. MRI predictions generalized more robustly to the test set. PSP leads to neurodegeneration in motor, cognitive and ocular motor networks at cortical and subcortical foci, leading to diverse yet overlapping clinical syndromes. To advance understanding of phenotypic heterogeneity in PSP, it is essential to consider data-driven approaches to clinical neuroimaging analyses.

Background: Conventional normative samples include individuals with undetected Alzheimer’s disease neuropathology, lowering test sensitivity for cognitive impairment. Objective: We developed Mayo Normative Studies (MNS) norms limited to individuals without elevated amyloid or neurodegeneration (A–N–) for Rey’s Auditory Verbal Learning Test (AVLT). We compared these MNS A–N– norms in female, male, and total samples to conventional MNS norms with varying levels of demographic adjustments. Methods: The A–N– sample included 1,059 Mayo Clinic Study of Aging cognitively unimpaired (CU) participants living in Olmsted County, MN, who are predominantly non-Hispanic White. Using a regression-based approach correcting for age, sex, and education, we derived fully-adjusted T-score formulas for AVLT variables. We validated these A–N– norms in two independent samples of CU ( n = 261) and mild cognitive impairment (MCI)/dementia participants ( n = 392) > 55 years of age. Results: Variability associated with age decreased by almost half in the A–N– norm sample relative to the conventional norm sample. Fully-adjusted MNS A–N– norms showed approximately 7– 9% higher sensitivity to MCI/dementia compared to fully-adjusted MNS conventional norms for trials 1– 5 total and sum of trials. Among women, sensitivity to MCI/dementia increased with each normative data refinement. In contrast, age-adjusted conventional MNS norms showed greatest sensitivity to MCI/dementia in men. Conclusions: A–N– norms show some benefits over conventional normative approaches to MCI/dementia sensitivity, especially for women. We recommend using these MNS A–N– norms alongside MNS conventional norms. Future work is needed to determine if normative samples that are not well characterized clinically show greater benefit from biomarker-refined approaches.

Abstract The National Institute on Aging and the Alzheimer's Association convened three separate work groups in 2011 and single work groups in 2012 and 2018 to create recommendations for the diagnosis and characterization of Alzheimer's disease (AD). The present document updates the 2018 research framework in response to several recent developments. Defining diseases biologically, rather than based on syndromic presentation, has long been standard in many areas of medicine (e.g., oncology), and is becoming a unifying concept common to all neurodegenerative diseases, not just AD. The present document is consistent with this principle. Our intent is to present objective criteria for diagnosis and staging AD, incorporating recent advances in biomarkers, to serve as a bridge between research and clinical care. These criteria are not intended to provide step‐by‐step clinical practice guidelines for clinical workflow or specific treatment protocols, but rather serve as general principles to inform diagnosis and staging of AD that reflect current science. Highlights We define Alzheimer's disease (AD) to be a biological process that begins with the appearance of AD neuropathologic change (ADNPC) while people are asymptomatic. Progression of the neuropathologic burden leads to the later appearance and progression of clinical symptoms. Early‐changing Core 1 biomarkers (amyloid positron emission tomography [PET], approved cerebrospinal fluid biomarkers, and accurate plasma biomarkers [especially phosphorylated tau 217]) map onto either the amyloid beta or AD tauopathy pathway; however, these reflect the presence of ADNPC more generally (i.e., both neuritic plaques and tangles). An abnormal Core 1 biomarker result is sufficient to establish a diagnosis of AD and to inform clinical decision making throughout the disease continuum. Later‐changing Core 2 biomarkers (biofluid and tau PET) can provide prognostic information, and when abnormal, will increase confidence that AD is contributing to symptoms. An integrated biological and clinical staging scheme is described that accommodates the fact that common copathologies, cognitive reserve, and resistance may modify relationships between clinical and biological AD stages.

AbstractINTRODUCTIONCorticobasal syndrome (CBS) can result from underlying Alzheimer's disease (AD) pathologies. Little is known about the utility of blood plasma metrics to predict positron emission tomography (PET) biomarker‐confirmed AD in CBS.METHODSA cohort of eighteen CBS patients (8 amyloid beta [Aβ]+; 10 Aβ−) and 8 cognitively unimpaired (CU) individuals underwent PET imaging and plasma analysis. Plasma concentrations were compared using a Kruskal–Wallis test. Spearman correlations assessed relationships between plasma concentrations and PET uptake.RESULTSCBS Aβ+ group showed a reduced Aβ42/40 ratio, with elevated phosphorylated tau (p‐tau)181, glial fibrillary acidic protein (GFAP), and neurofilament light (NfL) concentrations, while CBS Aβ− group only showed elevated NfL concentration compared to CU. Both p‐tau181 and GFAP were able to differentiate CBS Aβ− from CBS Aβ+ and showed positive associations with Aβ and tau PET uptake.DISCUSSIONThis study supports use of plasma p‐tau181 and GFAP to detect AD in CBS. NfL shows potential as a non‐specific disease biomarker of CBS regardless of underlying pathology.Highlights Plasma phosphorylated tau (p‐tau)181 and glial fibrillary acidic protein (GFAP) concentrations differentiate corticobasal syndrome (CBS) amyloid beta (Aβ)− from CBS Aβ+. Plasma neurofilament light concentrations are elevated in CBS Aβ− and Aβ+ compared to controls. Plasma p‐tau181 and GFAP concentrations were associated with Aβ and tau positron emission tomography (PET) uptake. Aβ42/40 ratio showed a negative correlation with Aβ PET uptake.

Abstract Hub regions in the brain, recognized for their roles in ensuring efficient information transfer, are vulnerable to pathological alterations in neurodegenerative conditions, including Alzheimer’s disease (AD). Computational simulations and animal experiments have hinted at the theory of activity-dependent degeneration as the cause of this hub vulnerability. However, two critical issues remain unresolved. First, past research has not clearly distinguished between two scenarios: hub regions facing a higher risk of connectivity disruption (targeted attack) and all regions having an equal risk (random attack). Second, human studies offering support for activity-dependent explanations remain scarce. We refined the hub disruption index to demonstrate a hub disruption pattern in functional connectivity in autosomal dominant AD that aligned with targeted attacks. This hub disruption is detectable even in preclinical stages, 12 years before the expected symptom onset and is amplified alongside symptomatic progression. Moreover, hub disruption was primarily tied to regional differences in global connectivity and sequentially followed changes observed in amyloid-beta positron emission tomography cortical markers, consistent with the activity-dependent degeneration explanation. Taken together, our findings deepen the understanding of brain network organization in neurodegenerative diseases and could be instrumental in refining diagnostic and targeted therapeutic strategies for AD in the future.

AbstractProgressive apraxia of speech (PAOS) is a 4R tauopathy characterized by difficulties with motor speech planning. Neurodegeneration in PAOS targets the premotor cortex, particularly the supplementary motor area (SMA), with degeneration of white matter (WM) tracts connecting premotor and motor cortices and Broca's area observed on diffusion tensor imaging (DTI). We aimed to assess flortaucipir uptake across speech‐language‐related WM tracts identified using DTI tractography in PAOS. Twenty‐two patients with PAOS and 26 matched healthy controls were recruited by the Neurodegenerative Research Group (NRG) and underwent MRI and flortaucipir‐PET. The patient population included patients with primary progressive apraxia of speech (PPAOS) and non‐fluent variant/agrammatic primary progressive aphasia (agPPA). Flortaucipir PET scans and DTI were coregistered using rigid registration with a mutual information cost function in subject space. Alignments between DTI and flortaucipir PET were inspected in all cases. Whole‐brain tractography was calculated using deterministic algorithms by a tractography reconstruction tool (DSI‐studio) and specific tracts were identified using an automatic fiber tracking atlas‐based method. Fractional anisotropy (FA) and flortaucipir standardized uptake value ratios (SUVRs) were averaged across the frontal aslant tract, arcuate fasciculi, inferior frontal‐occipital fasciculus, inferior and middle longitudinal fasciculi, as well as the SMA commissural fibers. Reduced FA (p < .0001) and elevated flortaucipir SUVR (p = .0012) were observed in PAOS cases compared to controls across all combined WM tracts. For flortaucipir SUVR, the greatest differentiation of PAOS from controls was achieved with the SMA commissural fibers (area under the receiver operator characteristic curve [AUROC] = 0.83), followed by the left arcuate fasciculus (AUROC = 0.75) and left frontal aslant tract (AUROC = 0.71). Our findings demonstrate that flortaucipir uptake is increased across WM tracts related to speech/language difficulties in PAOS.