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Obstructive sleep apnoea (OSA) is associated with an increased risk for cognitive impairment and dementia, which likely involves Alzheimer's disease pathology. Non-rapid eye movement slow-wave activity (SWA) has been implicated in amyloid clearance, but it has not been studied in the context of longitudinal amyloid accumulation in OSA. This longitudinal retrospective study aims to investigate the relationship between polysomnographic and electrophysiological SWA features and amyloid accumulation. From the Mayo Clinic Study of Aging cohort, we identified 71 participants ≥60 years old with OSA (mean baseline age = 72.9 ± 7.5 years, 60.6% male, 93% cognitively unimpaired) who had at least 2 consecutive Amyloid Pittsburgh Compound B (PiB)-PET scans and a polysomnographic study within 5 years of the baseline scan and before the second scan. Annualized PiB-PET accumulation [global ΔPiB(log)/year] was estimated by the difference between the second and first log-transformed global PiB-PET uptake estimations divided by the interval between scans (years). Sixty-four participants were included in SWA analysis. SWA was characterized by the mean relative spectral power density (%) in slow oscillation (SO: 0.5-0.9 Hz) and delta (1-3.9 Hz) frequency bands and by their downslopes (SO-slope and delta-slope, respectively) during the diagnostic portion of polysomnography. We fit linear regression models to test for associations among global ΔPiB(log)/year, SWA features (mean SO% and delta% or mean SO-slope and delta-slope), and OSA severity markers, after adjusting for age at baseline PiB-PET, APOE ɛ4 and baseline amyloid positivity. For 1 SD increase in SO% and SO-slope, global ΔPiB(log)/year increased by 0.0033 (95% CI: 0.0001; 0.0064, P = 0.042) and 0.0069 (95% CI: 0.0009; 0.0129, P = 0.026), which were comparable to 32% and 59% of the effect size associated with baseline amyloid positivity, respectively. Delta-slope was associated with a reduction in global ΔPiB(log)/year by -0.0082 (95% CI: -0.0143; -0.0021, P = 0.009). Sleep apnoea severity was not associated with amyloid accumulation. Regional associations were stronger in the pre-frontal region. Both slow-wave slopes had more significant and widespread regional associations. Annualized PiB-PET accumulation was positively associated with SO and SO-slope, which may reflect altered sleep homeostasis due to increased homeostatic pressure in the setting of unmet sleep needs, increased synaptic strength, and/or hyper-excitability in OSA. Delta-slope was inversely associated with PiB-PET accumulation, suggesting it may represent residual physiological activity. Further investigation of SWA dynamics in the presence of sleep disorders before and after treatment is necessary for understanding the relationship between amyloid accumulation and SWA physiology., Competing Interests: D.Z.C. is supported by the NIA/NIH. E.K.S. has received research support from the Mayo Clinic CCaTS, NIH, Michael J. Fox Foundation and Sunovion, Inc. M.M.M. is supported by the NIA/NIH. B.F.B. has served as an investigator for clinical trials sponsored by Alector, Biogen, Cognition Therapeutics, EIP Pharma and Transposon and served on the Scientific Advisory Board of the Tau Consortium. R.C.P. has served as a consultant for Roche, Inc., Merck, Inc., Genentech, Inc., Biogen, Inc. and GE Healthcare and received royalties from the Oxford University Press for the publication of Mild Cognitive Impairment. V.J.L. has served as a consultant for Bayer Schering Pharma, Piramal Life Sciences, Life Molecular Imaging, Eisai Inc., Eli Lilly, AVID Radiopharmaceuticals and Merck Research and received research support from GE Healthcare, Siemens Molecular Imaging, AVID Radiopharmaceuticals and the NIH. C.R.J. is supported by the NIA/NIH. J.G.-R. is supported by the NIH. He is on the drug safety medical board for NINDS and is the site PI for a clinical trial funded by Eisai. G.A.W. is supported by the NIH. He has licenced intellectual property to NeuroOne Inc. and Cadence Neuroscience Inc. He has served on the Scientific Advisory Boards for LivaNova Inc., NeuroPace Inc., UNEEG Inc and NeuroOne Inc. He has received royalties from NeuroOne Inc. V.K.S. has served as a consultant for ResMed, Zoll, Bayer, Lilly, Huxley, Apnimed, Jazz Pharmaceuticals and Axsome and is on the Scientific Advisory Board for Sleep Number Corporation. A.W.V. has served as a consultant for Jazz Pharmaceuticals. He is supported by R01 AG066870 and R01 AG080609. P.V. is supported by the NIA/NIH. The remaining authors report no competing interests., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Guarantors of Brain.)

There is increasing interest in Alzheimer's disease related plasma biomarkers due to their accessibility and scalability. We hypothesized that integrating plasma biomarkers with other commonly used and available participant data (MRI, cardiovascular factors, lifestyle, genetics) using machine learning (ML) models can improve individual prediction of cognitive outcomes. Further, our goal was to evaluate the heterogeneity of these predictors across different age strata. This longitudinal study included 1185 participants from the Mayo Clinic Study of Aging who had complete plasma analyte work-up at baseline. We used the Quanterix Simoa immunoassay to measure neurofilament light, Aβ 1-42 and Aβ 1-40 (used as Aβ 42 /Aβ 40 ratio), glial fibrillary acidic protein, and phosphorylated tau 181 (p-tau181). Participants' brain health was evaluated through gray and white matter structural MRIs. The study also considered cardiovascular factors (hyperlipidemia, hypertension, stroke, diabetes, chronic kidney disease), lifestyle factors (area deprivation index, body mass index, cognitive and physical activities), and genetic factors ( APOE , single nucleotide polymorphisms, and polygenic risk scores). An ML model was developed to predict cognitive outcomes at baseline and decline (slope). Three models were created: a base model with groups of risk factors as predictors, an enhanced model included socio-demographics, and a final enhanced model by incorporating plasma and socio-demographics into the base models. Models were explained for three age strata: younger than 65 years, 65-80 years, and older than 80 years, and further divided based on amyloid positivity status. Regardless of amyloid status the plasma biomarkers showed comparable performance ( R ² = 0.15) to MRI ( R ² = 0.18) and cardiovascular measures ( R ² = 0.10) when predicting cognitive decline. Inclusion of cardiovascular or MRI measures with plasma in the presence of socio-demographic improved cognitive decline prediction ( R ² = 0.26 and 0.27). For amyloid positive individuals Aβ 42 /Aβ 40 , glial fibrillary acidic protein and p-tau181 were the top predictors of cognitive decline while Aβ 42 /Aβ 40 was prominent for amyloid negative participants across all age groups. Socio-demographics explained a large portion of the variance in the amyloid negative individuals while the plasma biomarkers predominantly explained the variance in amyloid positive individuals (21% to 37% from the younger to the older age group). Plasma biomarkers performed similarly to MRI and cardiovascular measures when predicting cognitive outcomes and combining them with either measure resulted in better performance. Top predictors were heterogeneous between cross-sectional and longitudinal cognition models, across age groups, and amyloid status. Multimodal approaches will enhance the usefulness of plasma biomarkers through careful considerations of a study population's socio-demographics, brain and cardiovascular health., Competing Interests: There are no relevant disclosures relevant to this publication., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Guarantors of Brain.)

Predominant limbic degeneration has been associated with various underlying aetiologies and an older age, predominant impairment of episodic memory and slow clinical progression. However, the neurological syndrome associated with predominant limbic degeneration is not defined. This endeavour is critical to distinguish such a syndrome from those originating from neocortical degeneration, which may differ in underlying aetiology, disease course and therapeutic needs. We propose a set of clinical criteria for a limbic-predominant amnestic neurodegenerative syndrome that is highly associated with limbic-predominant age-related TDP-43 encephalopathy but also other pathologic entities. The criteria incorporate core, standard and advanced features, including older age at evaluation, mild clinical syndrome, disproportionate hippocampal atrophy, impaired semantic memory, limbic hypometabolism, absence of neocortical degeneration and low likelihood of neocortical tau, with degrees of certainty (highest, high, moderate and low). We operationalized this set of criteria using clinical, imaging and biomarker data to validate its associations with clinical and pathologic outcomes. We screened autopsied patients from Mayo Clinic and Alzheimer's Disease Neuroimaging Initiative cohorts and applied the criteria to those with an antemortem predominant amnestic syndrome (Mayo, n = 165; Alzheimer's Disease Neuroimaging Initiative, n = 53) and who had Alzheimer's disease neuropathological change, limbic-predominant age-related TDP-43 encephalopathy or both pathologies at autopsy. These neuropathology-defined groups accounted for 35, 37 and 4% of cases in the Mayo cohort, respectively, and 30, 22 and 9% of cases in the Alzheimer's Disease Neuroimaging Initiative cohort, respectively. The criteria effectively categorized these cases, with Alzheimer's disease having the lowest likelihoods, limbic-predominant age-related TDP-43 encephalopathy patients having the highest likelihoods and patients with both pathologies having intermediate likelihoods. A logistic regression using the criteria features as predictors of TDP-43 achieved a balanced accuracy of 74.6% in the Mayo cohort, and out-of-sample predictions in an external cohort achieved a balanced accuracy of 73.3%. Patients with high likelihoods had a milder and slower clinical course and more severe temporo-limbic degeneration compared to those with low likelihoods. Stratifying patients with both Alzheimer's disease neuropathological change and limbic-predominant age-related TDP-43 encephalopathy from the Mayo cohort according to their likelihoods revealed that those with higher likelihoods had more temporo-limbic degeneration and a slower rate of decline and those with lower likelihoods had more lateral temporo-parietal degeneration and a faster rate of decline. The implementation of criteria for a limbic-predominant amnestic neurodegenerative syndrome has implications to disambiguate the different aetiologies of progressive amnestic presentations in older age and guide diagnosis, prognosis, treatment and clinical trials., Competing Interests: V.J.L. consults for Bayer Schering Pharma, Piramal Life Sciences, Life Molecular Imaging, Eisai Inc., Avid Radiopharmaceuticals and Merck Research and receives research support from GE Healthcare, Siemens Molecular Imaging, Avid Radiopharmaceuticals and the NIH (NIA, NCI). D.S.K. serves on a Data Safety Monitoring Board for the DIAN study and for a tau therapeutic for Biogen but receives no personal compensation; is an investigator in clinical trials sponsored by Biogen, Lilly Pharmaceuticals and the University of Southern California; has served as a consultant for Roche, Samus Therapeutics, Third Rock and Alzeca Biosciences but receives no personal compensation; and receives funding from the NIH. B.F.B. receives honorarium for SAB activities for the Tau Consortium, is an investigator in clinical trials sponsored by Alector, Biogen, Cognition Therapeutics, EIP Pharma and Transposon and receives funding from the NIH. C.R.J. has no commercial conflicts and receives research support from the NIH, the GHR Foundation and the Alexander Family Alzheimer’s Disease Research Professorship of the Mayo Clinic. R.C.P. consults for Roche, Inc.; Merck, Inc.; Biogen, Inc.; Genentech, Inc.; Eisai, Inc.; and Nestle, Inc. but does not receive significant fees due to NIH limitations from the U24 AG057437 Co-PI role., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Guarantors of Brain.)

There is a longstanding ambiguity regarding the clinical diagnosis of dementia syndromes predominantly targeting executive functions versus behaviour and personality. This is due to an incomplete understanding of the macro-scale anatomy underlying these symptomatologies, a partial overlap in clinical features and the fact that both phenotypes can emerge from the same pathology and vice versa. We collected data from a patient cohort of which 52 had dysexecutive Alzheimer's disease, 30 had behavioural variant frontotemporal dementia (bvFTD), seven met clinical criteria for bvFTD but had Alzheimer's disease pathology (behavioural Alzheimer's disease) and 28 had amnestic Alzheimer's disease. We first assessed group-wise differences in clinical and cognitive features and patterns of fluorodeoxyglucose (FDG) PET hypometabolism. We then performed a spectral decomposition of covariance between FDG-PET images to yield latent patterns of relative hypometabolism unbiased by diagnostic classification, which are referred to as 'eigenbrains'. These eigenbrains were subsequently linked to clinical and cognitive data and meta-analytic topics from a large external database of neuroimaging studies reflecting a wide range of mental functions. Finally, we performed a data-driven exploratory linear discriminant analysis to perform eigenbrain-based multiclass diagnostic predictions. Dysexecutive Alzheimer's disease and bvFTD patients were the youngest at symptom onset, followed by behavioural Alzheimer's disease, then amnestic Alzheimer's disease. Dysexecutive Alzheimer's disease patients had worse cognitive performance on nearly all cognitive domains compared with other groups, except verbal fluency which was equally impaired in dysexecutive Alzheimer's disease and bvFTD. Hypometabolism was observed in heteromodal cortices in dysexecutive Alzheimer's disease, temporo-parietal areas in amnestic Alzheimer's disease and frontotemporal areas in bvFTD and behavioural Alzheimer's disease. The unbiased spectral decomposition analysis revealed that relative hypometabolism in heteromodal cortices was associated with worse dysexecutive symptomatology and a lower likelihood of presenting with behaviour/personality problems, whereas relative hypometabolism in frontotemporal areas was associated with a higher likelihood of presenting with behaviour/personality problems but did not correlate with most cognitive measures. The linear discriminant analysis yielded an accuracy of 82.1% in predicting diagnostic category and did not misclassify any dysexecutive Alzheimer's disease patient for behavioural Alzheimer's disease and vice versa. Our results strongly suggest a double dissociation in that distinct macro-scale underpinnings underlie predominant dysexecutive versus personality/behavioural symptomatology in dementia syndromes. This has important implications for the implementation of criteria to diagnose and distinguish these diseases and supports the use of data-driven techniques to inform the classification of neurodegenerative diseases., (© The Author(s) 2023. Published by Oxford University Press on behalf of the Guarantors of Brain.)

Given the prevalence of dementia and the development of pathology-specific disease-modifying therapies, high-value biomarker strategies to inform medical decision-making are critical. In vivo tau-PET is an ideal target as a biomarker for Alzheimer's disease diagnosis and treatment outcome measure. However, tau-PET is not currently widely accessible to patients compared to other neuroimaging methods. In this study, we present a convolutional neural network (CNN) model that imputes tau-PET images from more widely available cross-modality imaging inputs. Participants (n = 1192) with brain T1-weighted MRI (T1w), fluorodeoxyglucose (FDG)-PET, amyloid-PET and tau-PET were included. We found that a CNN model can impute tau-PET images with high accuracy, the highest being for the FDG-based model followed by amyloid-PET and T1w. In testing implications of artificial intelligence-imputed tau-PET, only the FDG-based model showed a significant improvement of performance in classifying tau positivity and diagnostic groups compared to the original input data, suggesting that application of the model could enhance the utility of the metabolic images. The interpretability experiment revealed that the FDG- and T1w-based models utilized the non-local input from physically remote regions of interest to estimate the tau-PET, but this was not the case for the Pittsburgh compound B-based model. This implies that the model can learn the distinct biological relationship between FDG-PET, T1w and tau-PET from the relationship between amyloid-PET and tau-PET. Our study suggests that extending neuroimaging's use with artificial intelligence to predict protein specific pathologies has great potential to inform emerging care models., (© The Author(s) 2023. Published by Oxford University Press on behalf of the Guarantors of Brain.)

Disruption of the default mode network is a hallmark of Alzheimer's disease, which has not been extensively examined in atypical phenotypes. We investigated cross-sectional and 1-year longitudinal changes in default mode network sub-systems in the visual and language variants of Alzheimer's disease, in relation to age and tau. Sixty-one amyloid-positive Alzheimer's disease participants diagnosed with posterior cortical atrophy ( n = 33) or logopenic progressive aphasia ( n = 28) underwent structural MRI, resting-state functional MRI and [ 18 F]flortaucipir PET. One-hundred and twenty-two amyloid-negative cognitively unimpaired individuals and 60 amyloid-positive individuals diagnosed with amnestic Alzheimer's disease were included as controls and as a comparison group, respectively, and had structural and resting-state functional MRI. Forty-one atypical Alzheimer's disease participants, 26 amnestic Alzheimer's disease participants and 40 cognitively unimpaired individuals had one follow-up functional MRI ∼1-2 years after the baseline scan. Default mode network connectivity was calculated using the dual regression method for posterior, ventral, anterior ventral and anterior dorsal sub-systems derived from independent component analysis. A global measure of default mode network connectivity, the network failure quotient, was also calculated. Linear mixed-effects models and voxel-based analyses were computed for each connectivity measure. Both atypical and amnestic Alzheimer's disease participants had lower cross-sectional posterior and ventral and higher anterior dorsal connectivity and network failure quotient relative to cognitively unimpaired individuals. Age had opposite effects on connectivity in Alzheimer's disease participants and cognitively unimpaired individuals. While connectivity declined with age in cognitively unimpaired individuals, younger Alzheimer's disease participants had lower connectivity than the older ones, particularly in the ventral default mode network. Greater baseline tau-PET uptake was associated with lower ventral and anterior ventral default mode network connectivity in atypical Alzheimer's disease. Connectivity in the ventral default mode network declined over time in atypical Alzheimer's disease, particularly in older participants, with lower tau burden. Voxel-based analyses validated the findings of higher anterior dorsal default mode network connectivity, lower posterior and ventral default mode network connectivity and decline in ventral default mode network connectivity over time in atypical Alzheimer's disease. Visuospatial symptoms were associated with default mode network connectivity disruption. In summary, default mode connectivity disruption was similar between atypical and amnestic Alzheimer's disease variants, and discriminated Alzheimer's disease from cognitively unimpaired individuals, with decreased posterior and increased anterior connectivity and with disruption more pronounced in younger participants. The ventral default mode network declined over time in atypical Alzheimer's disease, suggesting a shift in default mode network connectivity likely related to tau pathology., Competing Interests: I.S., N.C.-L., N.A.S. and J.L.G. have no disclosures to report. J.L.W., K.A.J., J.G.-R., C.G.S., M.M.M., D.T.J., H.B. and C.R.J. reported receiving research funding from the NIH. J.G.-R. is DSMB for NINDS STROKENE. V.J.L. reported consulting for Bayer Schering Pharma, Piramal Life Sciences, Life Molecular Imaging, Eisai Inc., AVID Radiopharmaceuticals and Merck Research and receiving research support from GE Healthcare, Siemens Molecular Imaging, AVID Radiopharmaceuticals and the NIH (NIA, NCI). R.C.P. has consulted for Roche, Inc., Merck, Inc., Biogen, Inc., Eisai, Inc., Nestle, Inc., and Genentech, Inc., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Guarantors of Brain.)

Blood-based biomarkers offer strong potential to revolutionize diagnosis, trial enrolment and treatment monitoring in Alzheimer's disease (AD). However, further advances are needed before these biomarkers can achieve wider deployment beyond selective research studies and specialty memory clinics, including the development of frameworks for optimal interpretation of biomarker profiles. We hypothesized that integrating Alzheimer's disease genetic risk score (AD-GRS) data would enhance the diagnostic value of plasma AD biomarkers by better capturing extant disease heterogeneity. Analysing 962 individuals from a population-based sample, we observed that an AD-GRS was independently associated with amyloid PET levels (an early marker of AD pathophysiology) over and above APOE ε4 or plasma p-tau181, amyloid-β42/40, glial fibrillary acidic protein or neurofilament light chain. Among individuals with a high or moderately high plasma p-tau181, integrating AD-GRS data significantly improved classification accuracy of amyloid PET positivity, including the finding that the combination of a high AD-GRS and high plasma p-tau181 outperformed p-tau181 alone in classifying amyloid PET positivity (88% versus 68%; P = 0.001). A machine learning approach incorporating plasma biomarkers, demographics and the AD-GRS was highly accurate in predicting amyloid PET levels (90% training set; 89% test set) and Shapley value analyses (an explainer method based in cooperative game theory) indicated that the AD-GRS and plasma biomarkers had differential importance in explaining amyloid deposition across individuals. Polygenic risk for AD dementia appears to account for a unique portion of disease heterogeneity, which could non-invasively enhance the interpretation of blood-based AD biomarker profiles in the population., (© The Author(s) 2023. Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Posterior cortical atrophy and logopenic progressive aphasia are atypical clinical presentations of Alzheimer's disease. Resting-state functional connectivity studies have shown functional network disruptions in both phenotypes, particularly involving the language network in logopenic progressive aphasia and the visual network in posterior cortical atrophy. However, little is known about how connectivity differs both within and between brain networks in these atypical Alzheimer's disease phenotypes. A cohort of 144 patients was recruited by the Neurodegenerative Research Group at Mayo Clinic, Rochester, MN, USA, and underwent structural and resting-state functional MRI. Spatially preprocessed data were analysed to explore the default mode network and the salience, sensorimotor, language, visual and memory networks. The data were analysed at the voxel and network levels. Bayesian hierarchical linear models adjusted for age and sex were used to analyse within- and between-network connectivity. Reduced within-network connectivity was observed in the language network in both phenotypes, with stronger evidence of reductions in logopenic progressive aphasia compared to controls. Only posterior cortical atrophy showed reduced within-network connectivity in the visual network compared to controls. Both phenotypes showed reduced within-network connectivity in the default mode and sensorimotor networks. No significant change was noted in the memory network, but a slight increase in the salience within-network connectivity was seen in both phenotypes compared to controls. Between-network analysis in posterior cortical atrophy showed evidence of reduced visual-to-language network connectivity, with reduced visual-to-salience network connectivity, compared to controls. An increase in visual-to-default mode network connectivity was noted in posterior cortical atrophy compared to controls. Between-network analysis in logopenic progressive aphasia showed evidence of reduced language-to-visual network connectivity and an increase in language-to-salience network connectivity compared to controls. Findings from the voxel-level and network-level analysis were in line with the Bayesian hierarchical linear model analysis, showing reduced connectivity in the dominant network based on diagnosis and more crosstalk between networks in general compared to controls. The atypical Alzheimer's disease phenotypes were associated with disruptions in connectivity, both within and between brain networks. Phenotype-specific differences in connectivity patterns were noted in the visual network for posterior cortical atrophy and the language network for logopenic progressive aphasia., Competing Interests: N.A.S., I.S., J.R.D., H.B., D.T.J., J.L.G. and P.R.M. have no disclosures to report. J.L.W., M.M.M. and K.A.J. reported receiving research funding from the NIH. J.G.-R. reported receiving research support from the NIH, and he also serves as an editorial board member for Neurology. C.R.J.J. reported serving on an independent data monitoring board for Roche and has consulted for and served as a speaker for Eisai and consulted for Biogen, but he receives no personal compensation from any commercial entity. He receives research support from the NIH, the GHR Foundation and the Alexander Family Alzheimer’s Disease Research Professorship of the Mayo Clinic. V.J.L. reported consulting for Bayer Schering Pharma, Piramal Life Sciences, Life Molecular Imaging, Eisai Inc., AVID Radiopharmaceuticals and Merck Research and receiving research support from GE Healthcare, Siemens Molecular Imaging, AVID Radiopharmaceuticals and the NIH (NIA, NCI)., (© The Author(s) 2023. Published by Oxford University Press on behalf of the Guarantors of Brain.)

Dysexecutive Alzheimer's disease (dAD) manifests as a progressive dysexecutive syndrome without prominent behavioral features, and previous studies suggest clinico-radiological heterogeneity within this syndrome. We uncovered this heterogeneity using unsupervised machine learning in 52 dAD patients with multimodal imaging and cognitive data. A spectral decomposition of covariance between FDG-PET images yielded six latent factors ("eigenbrains") accounting for 48% of variance in patterns of hypometabolism. These eigenbrains differentially related to age at onset, clinical severity, and cognitive performance. A hierarchical clustering on the eigenvalues of these eigenbrains yielded four dAD subtypes, i.e. "left-dominant," "right-dominant," "bi-parietal-dominant," and "heteromodal-diffuse." Patterns of FDG-PET hypometabolism overlapped with those of tau-PET distribution and MRI neurodegeneration for each subtype, whereas patterns of amyloid deposition were similar across subtypes. Subtypes differed in age at onset and clinical severity where the heteromodal-diffuse exhibited a worse clinical picture, and the bi-parietal had a milder clinical presentation. We propose a conceptual framework of executive components based on the clinico-radiological associations observed in dAD. We demonstrate that patients with dAD, despite sharing core clinical features, are diagnosed with variability in their clinical and neuroimaging profiles. Our findings support the use of data-driven approaches to delineate brain-behavior relationships relevant to clinical practice and disease physiology., (© The Author(s) 2023. Published by Oxford University Press.)

Staging the severity of Alzheimer's disease pathology using biomarkers is useful for therapeutic trials and clinical prognosis. Disease staging with amyloid and tau PET has face validity; however, this would be more practical with plasma biomarkers. Our objectives were, first, to examine approaches for staging amyloid and tau PET and, second, to examine prediction of amyloid and tau PET stages using plasma biomarkers. Participants (n = 1136) were enrolled in either the Mayo Clinic Study of Aging or the Alzheimer's Disease Research Center; had a concurrent amyloid PET, tau PET and blood draw; and met clinical criteria for cognitively unimpaired (n = 864), mild cognitive impairment (n = 148) or Alzheimer's clinical syndrome with dementia (n = 124). The latter two groups were combined into a cognitively impaired group (n = 272). We used multinomial regression models to estimate discrimination [concordance (C) statistics] among three amyloid PET stages (low, intermediate, high), four tau PET stages (Braak 0, 1-2, 3-4, 5-6) and a combined amyloid and tau PET stage (none/low versus intermediate/high severity) using plasma biomarkers as predictors separately within unimpaired and impaired individuals. Plasma analytes, p-tau181, Aβ1-42 and Aβ1-40 (analysed as the Aβ42/Aβ40 ratio), glial fibrillary acidic protein and neurofilament light chain were measured on the HD-X Simoa Quanterix platform. Plasma p-tau217 was also measured in a subset (n = 355) of cognitively unimpaired participants using the Lilly Meso Scale Discovery assay. Models with all Quanterix plasma analytes along with risk factors (age, sex and APOE) most often provided the best discrimination among amyloid PET stages (C = 0.78-0.82). Models with p-tau181 provided similar discrimination of tau PET stages to models with all four plasma analytes (C = 0.72-0.85 versus C = 0.73-0.86). Discriminating a PET proxy of intermediate/high from none/low Alzheimer's disease neuropathological change with all four Quanterix plasma analytes was excellent but not better than p-tau181 only (C = 0.88 versus 0.87 for unimpaired and C = 0.91 versus 0.90 for impaired). Lilly p-tau217 outperformed the Quanterix p-tau181 assay for discriminating high versus intermediate amyloid (C = 0.85 versus 0.74) but did not improve over a model with all Quanterix plasma analytes and risk factors (C = 0.85 versus 0.83). Plasma analytes along with risk factors can discriminate between amyloid and tau PET stages and between a PET surrogate for intermediate/high versus none/low neuropathological change with accuracy in the acceptable to excellent range. Combinations of plasma analytes are better than single analytes for many staging predictions with the exception that Quanterix p-tau181 alone usually performed equivalently to combinations of Quanterix analytes for tau PET discrimination., (© The Author(s) 2023. Published by Oxford University Press on behalf of the Guarantors of Brain.)

From a complex systems perspective, clinical syndromes emerging from neurodegenerative diseases are thought to result from multiscale interactions between aggregates of misfolded proteins and the disequilibrium of large-scale networks coordinating functional operations underpinning cognitive phenomena. Across all syndromic presentations of Alzheimer's disease, age-related disruption of the default mode network is accelerated by amyloid deposition. Conversely, syndromic variability may reflect selective neurodegeneration of modular networks supporting specific cognitive abilities. In this study, we leveraged the breadth of the Human Connectome Project-Aging cohort of non-demented individuals ( N = 724) as a normative cohort to assess the robustness of a biomarker of default mode network dysfunction in Alzheimer's disease, the network failure quotient, across the aging spectrum. We then examined the capacity of the network failure quotient and focal markers of neurodegeneration to discriminate patients with amnestic ( N = 8) or dysexecutive ( N = 10) Alzheimer's disease from the normative cohort at the patient level, as well as between Alzheimer's disease phenotypes. Importantly, all participants and patients were scanned using the Human Connectome Project-Aging protocol, allowing for the acquisition of high-resolution structural imaging and longer resting-state connectivity acquisition time. Using a regression framework, we found that the network failure quotient related to age, global and focal cortical thickness, hippocampal volume, and cognition in the normative Human Connectome Project-Aging cohort, replicating previous results from the Mayo Clinic Study of Aging that used a different scanning protocol. Then, we used quantile curves and group-wise comparisons to show that the network failure quotient commonly distinguished both dysexecutive and amnestic Alzheimer's disease patients from the normative cohort. In contrast, focal neurodegeneration markers were more phenotype-specific, where the neurodegeneration of parieto-frontal areas associated with dysexecutive Alzheimer's disease, while the neurodegeneration of hippocampal and temporal areas associated with amnestic Alzheimer's disease. Capitalizing on a large normative cohort and optimized imaging acquisition protocols, we highlight a biomarker of default mode network failure reflecting shared system-level pathophysiological mechanisms across aging and dysexecutive and amnestic Alzheimer's disease and biomarkers of focal neurodegeneration reflecting distinct pathognomonic processes across the amnestic and dysexecutive Alzheimer's disease phenotypes. These findings provide evidence that variability in inter-individual cognitive impairment in Alzheimer's disease may relate to both modular network degeneration and default mode network disruption. These results provide important information to advance complex systems approaches to cognitive aging and degeneration, expand the armamentarium of biomarkers available to aid diagnosis, monitor progression and inform clinical trials., Competing Interests: C.R.J. serves as an independent data monitoring board for Roche, has served as a speaker for Eisai, and consulted for Biogen, but he receives no personal compensation from any commercial entity. He receives research support from NIH, the GHR Foundation and the Alexander Family Alzheimer’s Disease Research Professorship of the Mayo Clinic. C.G.S. receives research funding from the NIH., (© The Author(s) 2023. Published by Oxford University Press on behalf of the Guarantors of Brain.)

Mild cognitive impairment with the core clinical features of dementia with Lewy bodies is recognized as a prodromal stage of dementia with Lewy bodies. Although grey matter atrophy has been demonstrated in prodromal dementia with Lewy bodies, longitudinal rates of atrophy during progression to probable dementia with Lewy bodies are unknown. We investigated the regional patterns of cross-sectional and longitudinal rates of grey matter atrophy in prodromal dementia with Lewy bodies, including those who progressed to probable dementia with Lewy bodies. Patients with mild cognitive impairment with at least one core clinical feature of dementia with Lewy bodies (mean age = 70.5; 95% male), who were enrolled in the Mayo Clinic Alzheimer's Disease Research Center and followed for at least two clinical evaluations and MRI examinations, were included ( n  = 56). A cognitively unimpaired control group ( n  = 112) was matched 2:1 to the patients with mild cognitive impairment by age and sex. Patients either remained stable ( n  = 28) or progressed to probable dementia with Lewy bodies ( n  = 28) during a similar follow-up period and pathologic confirmation was available in a subset of cases ( n  = 18). Cross-sectional and longitudinal rates of grey matter atrophy were assessed using voxel-based and atlas-based region of interest analyses. At baseline, prodromal dementia with Lewy bodies was characterized by atrophy in the nucleus basalis of Meynert both in those who remained stable and those who progressed to probable dementia with Lewy bodies ( P  < 0.05 false discovery rate corrected). Increase in longitudinal grey matter atrophy rates were widespread, with greatest rates of atrophy observed in the enthorhinal and parahippocampal cortices, temporoparietal association cortices, thalamus and the basal ganglia, in mild cognitive impairment patients who progressed to probable dementia with Lewy bodies at follow-up ( P  < 0.05 false discovery rate corrected). Rates of inferior temporal atrophy were associated with greater rates of worsening on the clinical dementia rating-sum of boxes. Seventeen of the 18 (94%) autopsied cases had Lewy body disease. Results show that atrophy in the nucleus basalis of Meynert is a feature of prodromal dementia with Lewy bodies regardless of proximity to progression to probable dementia with Lewy bodies. Longitudinally, grey matter atrophy progresses in regions with significant cholinergic innervation, in alignment with clinical disease progression, with widespread and accelerated rates of atrophy in patients who progress to probable dementia with Lewy bodies. Given the prominent neurodegeneration in the cholinergic system, patients with prodromal dementia with Lewy bodies may be candidates for cholinesterase inhibitor treatment., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Guarantors of Brain.)

Dementia and mortality rates rise inexorably with age and consequently interact. However, because of the major logistical difficulties in accounting for both outcomes in a defined population, very little work has examined how risk factors and biomarkers for incident dementia are influenced by competing mortality. The objective of this study was to examine long-term associations between amyloid PET, APOE ɛ4, sex, education and cardiovascular/metabolic conditions, and hazard and absolute risk of dementia and mortality in individuals without dementia at enrolment. Participants were enrolled in the Mayo Clinic Study of Aging, a population-based study of cognitive ageing in Olmsted County, MN, USA. All were without dementia and were age 55-92 years at enrolment and were followed longitudinally. Predictor variables were amyloid PET, APOE ɛ4 status, sex, education, cardiovascular/metabolic conditions and age. The main outcomes were incident dementia and mortality. Multivariable, multi-state models were used to estimate mortality and incident dementia rates and absolute risk of dementia and mortality by predictor variable group. Of the 4984 participants in the study, 4336 (87%) were cognitively unimpaired and 648 (13%) had mild cognitive impairment at enrolment. The median age at enrolment was 75 years; 2463 (49%) were women. The median follow-up time was 9.4 years (7.5 years after PET). High versus normal amyloid (hazard ratio 2.11, 95% confidence interval 1.43-2.79), APOE ɛ4 (women: hazard ratio 2.24, 95% confidence interval 1.80-2.77; men: hazard ratio 1.37, 95% confidence interval 1.09-1.71), older age and two additional cardiovascular/metabolic conditions (hazard ratio 1.37, 95% confidence interval 1.22-1.53) were associated with the increased hazard of dementia (all P  < 0.001). Among APOE ɛ4 carriers with elevated amyloid, remaining lifetime risk of dementia at age 65 years was greater in women [74% (95% confidence interval 65-84%) high and 58% (95% confidence interval 52-65%) moderate amyloid], than men [62% (95% confidence interval 52-73%) high and 44% (95% confidence interval 35-53%) moderate amyloid]. Overall, the hazard and absolute risk of dementia varied considerably by predictor group. The absolute risk of dementia associated with predictors characteristic of Alzheimer's disease was greater in women than men while at the same time the combination of APOE ɛ4 non-carrier with normal amyloid was more protective in women than men. This set of findings may be attributed in part to different biological effects and in part to lower mortality rates in women., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Guarantors of Brain.)

Dementia with Lewy bodies (DLB) is neuropathologically defined by the presence of α-synuclein aggregates, but many DLB cases show concurrent Alzheimer's disease pathology in the form of amyloid-β plaques and tau neurofibrillary tangles. The first objective of this study was to investigate the effect of Alzheimer's disease co-pathology on functional network changes within the default mode network (DMN) in DLB. Second, we studied how the distribution of tau pathology measured with PET relates to functional connectivity in DLB. Twenty-seven DLB, 26 Alzheimer's disease and 99 cognitively unimpaired participants (balanced on age and sex to the DLB group) underwent tau-PET with AV-1451 (flortaucipir), amyloid-β-PET with Pittsburgh compound-B (PiB) and resting-state functional MRI scans. The resing-state functional MRI data were used to assess functional connectivity within the posterior DMN. This was then correlated with overall cortical flortaucipir PET and PiB PET standardized uptake value ratio (SUVr). The strength of interregional functional connectivity was assessed using the Schaefer atlas. Tau-PET covariance was measured as the correlation in flortaucipir SUVr between any two regions across participants. The association between region-to-region functional connectivity and tau-PET covariance was assessed using linear regression. Additionally, we identified the region with highest and the region with lowest tau SUVrs (tau hot- and cold spots) and tested whether tau SUVr in all other brain regions was associated with the strength of functional connectivity to these tau hot and cold spots. A reduction in posterior DMN connectivity correlated with overall higher cortical tau- (r = -0.39, P = 0.04) and amyloid-PET uptake (r = -0.41, P = 0.03) in the DLB group, i.e. patients with DLB who have more concurrent Alzheimer's disease pathology showed a more severe loss of DMN connectivity. Higher functional connectivity between regions was associated with higher tau covariance in cognitively unimpaired, Alzheimer's disease and DLB. Furthermore, higher functional connectivity of a target region to the tau hotspot (i.e. inferior/medial temporal cortex) was related to higher flortaucipir SUVrs in the target region, whereas higher functional connectivity to the tau cold spot (i.e. sensory-motor cortex) was related to lower flortaucipir SUVr in the target region. Our findings suggest that a higher burden of Alzheimer's disease co-pathology in patients with DLB is associated with more Alzheimer's disease-like changes in functional connectivity. Furthermore, we found an association between the brain's functional network architecture and the distribution of tau pathology that has recently been described in Alzheimer's disease. We show that this relationship also exists in patients with DLB, indicating that similar mechanisms of connectivity-dependent occurrence of tau pathology might be at work in both diseases., (© The Author(s) (2021). Published by Oxford University Press on behalf of the Guarantors of Brain.)

Posterior cortical atrophy is a neurodegenerative syndrome with a heterogeneous clinical presentation due to variable involvement of the left, right, dorsal and ventral parts of the visual system, as well as inconsistent involvement of other cognitive domains and systems. 18 F-fluorodeoxyglucose (FDG)-PET is a sensitive marker for regional brain damage or dysfunction, capable of capturing the pattern of neurodegeneration at the single-participant level. We aimed to leverage these inter-individual differences on FDG-PET imaging to better understand the associations of heterogeneity of posterior cortical atrophy. We identified 91 posterior cortical atrophy participants with FDG-PET data and abstracted demographic, neurologic, neuropsychological and Alzheimer's disease biomarker data. The mean age at reported symptom onset was 59.3 (range: 45-72 years old), with an average disease duration of 4.2 years prior to FDG-PET scan, and a mean education of 15.0 years. Females were more common than males at 1.6:1. After standard preprocessing steps, the FDG-PET scans for the cohort were entered into an unsupervised machine learning algorithm which first creates a high-dimensional space of inter-individual covariance before performing an eigen-decomposition to arrive at a low-dimensional representation. Participant values ('eigenbrains' or latent vectors which represent principle axes of inter-individual variation) were then compared to the clinical and biomarker data. Eight eigenbrains explained over 50% of the inter-individual differences in FDG-PET uptake with left (eigenbrain 1) and right (eigenbrain 2) hemispheric lateralization representing 24% of the variance. Furthermore, eigenbrain-loads mapped onto clinical and neuropsychological data (i.e. aphasia, apraxia and global cognition were associated with the left hemispheric eigenbrain 1 and environmental agnosia and apperceptive prosopagnosia were associated with the right hemispheric eigenbrain 2), suggesting that they captured important axes of normal and abnormal brain function. We used NeuroSynth to characterize the eigenbrains through topic-based decoding, which supported the idea that the eigenbrains map onto a diverse set of cognitive functions. These eigenbrains captured important biological and pathophysiologic data (i.e. limbic predominant eigenbrain 4 patterns being associated with older age of onset compared to frontoparietal eigenbrain 7 patterns being associated with younger age of onset), suggesting that approaches that focus on inter-individual differences may be important to better understand the variability observed within a neurodegenerative syndrome like posterior cortical atrophy., (© The Author(s) (2021). Published by Oxford University Press on behalf of the Guarantors of Brain.)

White matter microstructure undergoes progressive changes during the lifespan, but the neurobiological underpinnings related to ageing and disease remains unclear. We used an advanced diffusion MRI, Neurite Orientation Dispersion and Density Imaging, to investigate the microstructural alterations due to demographics, common age-related pathological processes (amyloid, tau and white matter hyperintensities) and cognition. We also compared Neurite Orientation Dispersion and Density Imaging findings to the older Diffusion Tensor Imaging model-based findings. Three hundred and twenty-eight participants (264 cognitively unimpaired, 57 mild cognitive impairment and 7 dementia with a mean age of 68.3 ± 13.1 years) from the Mayo Clinic Study of Aging with multi-shell diffusion imaging, fluid attenuated inversion recovery MRI as well as amyloid and tau PET scans were included in this study. White matter tract level diffusion measures were calculated from Diffusion Tensor Imaging and Neurite Orientation Dispersion and Density Imaging. Pearson correlation and multiple linear regression analyses were performed with diffusion measures as the outcome and age, sex, education/occupation, white matter hyperintensities, amyloid and tau as predictors. Analyses were also performed with each diffusion MRI measure as a predictor of cognitive outcomes. Age and white matter hyperintensities were the strongest predictors of all white matter diffusion measures with low associations with amyloid and tau. However, neurite density decrease from Neurite Orientation Dispersion and Density Imaging was observed with amyloidosis specifically in the temporal lobes. White matter integrity (mean diffusivity and free water) in the corpus callosum showed the greatest associations with cognitive measures. All diffusion measures provided information about white matter ageing and white matter changes due to age-related pathological processes and were associated with cognition. Neurite orientation dispersion and density imaging and diffusion tensor imaging are two different diffusion models that provide distinct information about variation in white matter microstructural integrity. Neurite Orientation Dispersion and Density Imaging provides additional information about synaptic density, organization and free water content which may aid in providing mechanistic insights into disease progression., (© The Author(s) (2021). Published by Oxford University Press on behalf of the Guarantors of Brain.)

While cerebrovascular disease can be observed in vivo using MRI, the multiplicity and heterogeneity in the mechanisms of cerebrovascular damage impede accounting for these measures in ageing and dementia studies. Our primary goal was to investigate the key sources of variability across MRI markers of cerebrovascular disease and evaluate their impact in comparison to amyloidosis on cognitive decline in a population-based sample. Our secondary goal was to evaluate the prognostic utility of a cerebrovascular summary measure from all markers. We included both visible lesions seen on MRI (white matter hyperintensities, cortical and subcortical infarctions, lobar and deep microbleeds) and early white matter damage due to systemic vascular health using diffusion changes in the genu of the corpus callosum. We identified 1089 individuals aged ≥60 years with concurrent amyloid-PET and MRI scans from the population-based Mayo Clinic Study of Aging. We divided these into discovery and validation datasets. Using the discovery dataset, we conducted principal component analyses and ascertained the main sources of variability in cerebrovascular disease markers. Using linear regression and mixed effect models, we evaluated the utility of these principal components and combinations of these components for the prediction of cognitive performance along with amyloidosis. Our main findings were (i) there were three primary sources of variability among the CVD measures-white matter changes are driven by white matter hyperintensities and diffusion changes; number of microbleeds (lobar and deep); and number of infarctions (cortical and subcortical); (ii) Components of white matter changes and microbleeds but not infarctions significantly predicted cognition trajectories in all domains with greater contributions from white matter; and (iii) The summary vascular score explained 3-5% of variability in baseline global cognition in comparison to 3-6% variability explained by amyloidosis. Across all cognitive domains, the vascular summary score had the least impact on memory performance (∼1%). Though there is mechanistic heterogeneity in the cerebrovascular disease markers measured on MRI, these changes can be grouped into three components and together explain variability in cognitive performance equivalent to the impact of amyloidosis on cognition. White matter changes represent dynamic ongoing damage, predicts future cognitive decline across all domains and diffusion measurements help capture white matter damage due to systemic vascular changes. Therefore, measuring and accounting for white matter changes using diffusion MRI and white matter hyperintensities along with microbleeds will allow us to capture vascular contributions to cognitive impairment and dementia., (© The Author(s) (2021). Published by Oxford University Press on behalf of the Guarantors of Brain.)

The mechanisms through which tau and amyloid-beta (Aβ) accumulate in the brain of Alzheimer's disease patients may differ but both are related to neuronal networks. We examined such mechanisms on neuroimaging in 58 participants with atypical Alzheimer's disease (posterior cortical atrophy or logopenic progressive aphasia). Participants underwent Aβ-PET, longitudinal tau-PET, structural MRI and resting-state functional MRI, which was analyzed with graph theory. Regions with high levels of Aβ were more likely to be functional hubs, with a high number of functional connections important for resilience to cascading network failures. Regions with high levels of tau were more likely to have low clustering coefficients and degrees, suggesting a lack of trophic support or vulnerability to local network failures. Regions strongly functionally connected to the disease epicenters were more likely to have higher levels of tau and, less strongly, of Aβ. The regional rate of tau accumulation was associated with tau levels in functionally connected regions, in support of tau accumulation in a functional network. This study elucidates the relations of tau and Aβ to functional connectivity metrics in atypical Alzheimer's disease, strengthening the hypothesis that the spread of the 2 proteins is driven by different biological mechanisms related to functional networks., (© The Author(s) 2020. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permission@oup.com.)

Deterioration in white-matter health plays a role in cognitive ageing. Our goal was to discern heterogeneity of white-matter tract vulnerability in ageing using longitudinal imaging data (two to five imaging and cognitive assessments per participant) from a population-based sample of 553 elderly participants (age ≥60 years). We found that different clusters (healthy white matter, fast white-matter decliners and intermediate white-matter group) were heterogeneous in the spatial distribution of white-matter integrity, systemic health and cognitive trajectories. White-matter health of specific tracts (genu of corpus callosum, posterior corona radiata and anterior internal capsule) informed about cluster assignments. Not surprisingly, brain amyloidosis was not significantly different between clusters. Clusters had differential white-matter tract vulnerability to ageing (commissural fibres > association/brainstem fibres). Identification of vulnerable white-matter tracts is a valuable approach to assessing risk for cognitive decline., (© The Author(s) (2021). Published by Oxford University Press on behalf of the Guarantors of Brain.)

Clinical trials with anti-tau drugs will need to target individuals at risk of accumulating tau. Our objective was to identify variables available in a research setting that predict future rates of tau PET accumulation separately among individuals who were either cognitively unimpaired or cognitively impaired. All 337 participants had: a baseline study visit with MRI, amyloid PET, and tau PET exams, at least one follow-up tau PET exam; and met clinical criteria for membership in one of two clinical diagnostic groups: cognitively unimpaired (n = 203); or cognitively impaired (n = 134, a combined group of participants with either mild cognitive impairment or dementia with Alzheimer's clinical syndrome). Our primary analyses were in these two clinical groups; however, we also evaluated subgroups dividing the unimpaired group by normal/abnormal amyloid PET and the impaired group by clinical phenotype (mild cognitive impairment, amnestic dementia, and non-amnestic dementia). Linear mixed effects models were used to estimate associations between age, sex, education, APOE genotype, amyloid and tau PET standardized uptake value ratio (SUVR), cognitive performance, cortical thickness, and white matter hyperintensity volume at baseline, and the rate of subsequent tau PET accumulation. Log-transformed tau PET SUVR was used as the response and rates were summarized as annual per cent change. A temporal lobe tau PET meta-region of interest was used. In the cognitively unimpaired group, only higher baseline amyloid PET was a significant independent predictor of higher tau accumulation rates (P < 0.001). Higher rates of tau accumulation were associated with faster rates of cognitive decline in the cognitively unimpaired subgroup with abnormal amyloid PET (P = 0.03), but among the subgroup with normal amyloid PET. In the cognitively impaired group, younger age (P = 0.02), higher baseline amyloid PET (P = 0.05), APOE ε4 (P = 0.05), and better cognitive performance (P = 0.05) were significant independent predictors of higher tau accumulation rates. Among impaired individuals, faster cognitive decline was associated with faster rates of tau accumulation (P = 0.01). While we examined many possible predictor variables, our results indicate that screening of unimpaired individuals for potential inclusion in anti-tau trials may be straightforward because the only independent predictor of high tau rates was amyloidosis. In cognitively impaired individuals, imaging and clinical variables consistent with early onset Alzheimer's disease phenotype were associated with higher rates of tau PET accumulation suggesting this may be a highly advantageous group in which to conduct proof-of-concept clinical trials that target tau-related mechanisms. The nature of the dementia phenotype (amnestic versus non-amnestic) did not affect this conclusion., (© The Author(s) (2020). Published by Oxford University Press on behalf of the Guarantors of Brain.)

Tau deposition is a key biological feature of Alzheimer's disease that is closely related to cognitive impairment. However, it remains poorly understood why certain individuals may be more susceptible to tau deposition while others are more resistant. The recent availability of in vivo assessment of tau burden through positron emission tomography provides an opportunity to test the hypothesis that common genetic variants may influence tau deposition. We performed a genome-wide association study of tau-positron emission tomography on a sample of 754 individuals over age 50 (mean age 72.4 years, 54.6% men, 87.6% cognitively unimpaired) from the population-based Mayo Clinic Study of Aging. Linear regression was performed to test nucleotide polymorphism associations with AV-1451 ( 18 F-flortaucipir) tau-positron emission tomography burden in an Alzheimer's-signature composite region of interest, using an additive genetic model and covarying for age, sex and genetic principal components. Genome-wide significant associations with higher tau were identified for rs76752255 ( P  =   9.91 × 10 -9 , β  = 0.20) in the tau phosphorylation regulatory gene PPP2R2B (protein phosphatase 2 regulatory subunit B) and for rs117402302 ( P   =   4.00 × 10 -8 , β  = 0.19) near IGF2BP3 (insulin-like growth factor 2 mRNA-binding protein 3). The PPP2R2B association remained genome-wide significant after additionally covarying for global amyloid burden and cerebrovascular disease risk, while the IGF2BP3 association was partially attenuated after accounting for amyloid load. In addition to these discoveries, three single nucleotide polymorphisms within MAPT (microtubule-associated protein tau) displayed nominal associations with tau-positron emission tomography burden, and the association of the APOE (apolipoprotein E) ɛ4 allele with tau-positron emission tomography was marginally nonsignificant ( P   =   0.06, β  = 0.07). No associations with tau-positron emission tomography burden were identified for other single nucleotide polymorphisms associated with Alzheimer's disease clinical diagnosis in prior large case-control studies. Our findings nominate PPP2R2B and IGF2BP3 as novel potential influences on tau pathology which warrant further functional characterization. Our data are also supportive of previous literature on the associations of MAPT genetic variation with tau, and more broadly supports the inference that tau accumulation may have a genetic architecture distinct from known Alzheimer's susceptibility genes, which may have implications for improved risk stratification and therapeutic targeting., (© The Author(s) (2020). Published by Oxford University Press on behalf of the Guarantors of Brain.)

Alzheimer's disease can present clinically with either the typical amnestic phenotype or with atypical phenotypes, such as logopenic progressive aphasia and posterior cortical atrophy. We have recently described longitudinal patterns of flortaucipir PET uptake and grey matter atrophy in the atypical phenotypes, demonstrating a longitudinal regional disconnect between flortaucipir accumulation and brain atrophy. However, it is unclear how these longitudinal patterns differ from typical Alzheimer's disease, to what degree flortaucipir and atrophy mirror clinical phenotype in Alzheimer's disease, and whether optimal longitudinal neuroimaging biomarkers would also differ across phenotypes. We aimed to address these unknowns using a cohort of 57 participants diagnosed with Alzheimer's disease (18 with typical amnestic Alzheimer's disease, 17 with posterior cortical atrophy and 22 with logopenic progressive aphasia) that had undergone baseline and 1-year follow-up MRI and flortaucipir PET. Typical Alzheimer's disease participants were selected to be over 65 years old at baseline scan, while no age criterion was used for atypical Alzheimer's disease participants. Region and voxel-level rates of tau accumulation and atrophy were assessed relative to 49 cognitively unimpaired individuals and among phenotypes. Principal component analysis was implemented to describe variability in baseline tau uptake and rates of accumulation and baseline grey matter volumes and rates of atrophy across phenotypes. The capability of the principal components to discriminate between phenotypes was assessed with logistic regression. The topography of longitudinal tau accumulation and atrophy differed across phenotypes, with key regions of tau accumulation in the frontal and temporal lobes for all phenotypes and key regions of atrophy in the occipitotemporal regions for posterior cortical atrophy, left temporal lobe for logopenic progressive aphasia and medial and lateral temporal lobe for typical Alzheimer's disease. Principal component analysis identified patterns of variation in baseline and longitudinal measures of tau uptake and volume that were significantly different across phenotypes. Baseline tau uptake mapped better onto clinical phenotype than longitudinal tau and MRI measures. Our study suggests that optimal longitudinal neuroimaging biomarkers for future clinical treatment trials in Alzheimer's disease are different for MRI and tau-PET and may differ across phenotypes, particularly for MRI. Baseline tau tracer retention showed the highest fidelity to clinical phenotype, supporting the important causal role of tau as a driver of clinical dysfunction in Alzheimer's disease., (© The Author(s) (2020). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Among individuals with dementia with Lewy bodies, pathologic correlates of clinical course include the presence and extent of coexisting Alzheimer's pathology and the presence of transitional or diffuse Lewy body disease. The objectives of this study are to determine (i) whether 18 F-fluorodeoxyglucose PET signature patterns of dementia with Lewy bodies are associated with the extent of coexisting Alzheimer's pathology and the presence of transitional or diffuse Lewy body disease and (ii) whether these 18 F-fluorodeoxyglucose pattern(s) are associated with clinical course in dementia with Lewy bodies. Two groups of participants were included: a pathology-confirmed subset with Lewy body disease ( n  = 34) and a clinically diagnosed group of dementia with Lewy bodies ( n  = 87). A subset of the clinically diagnosed group was followed longitudinally ( n  = 51). We evaluated whether 18 F-fluorodeoxyglucose PET features of dementia with Lewy bodies (higher cingulate island sign ratio and greater occipital hypometabolism) varied by Lewy body disease subtype (transitional versus diffuse) and Braak neurofibrillary tangle stage. We investigated whether the PET features were associated with the clinical trajectories by performing regression models predicting Clinical Dementia Rating Scale Sum of Boxes. Among autopsied participants, there was no difference in cingulate island sign or occipital hypometabolism by Lewy body disease type, but those with a lower Braak tangle stage had a higher cingulate island sign ratio compared to those with a higher Braak tangle stage. Among the clinically diagnosed dementia with Lewy bodies participants, a higher cingulate island ratio was associated with better cognitive scores at baseline and longitudinally. A higher 18 F-fluorodeoxyglucose PET cingulate island sign ratio was associated with lower Braak tangle stage at autopsy, predicted a better clinical trajectory in dementia with Lewy body patients and may allow for improved prognostication of the clinical course in this disease., (© The Author(s) (2020). Published by Oxford University Press on behalf of the Guarantors of Brain.)

We report a group of patients presenting with a progressive dementia syndrome characterized by predominant dysfunction in core executive functions, relatively young age of onset and positive biomarkers for Alzheimer's pathophysiology. Atypical frontal, dysexecutive/behavioural variants and early-onset variants of Alzheimer's disease have been previously reported, but no diagnostic criteria exist for a progressive dysexecutive syndrome. In this retrospective review, we report on 55 participants diagnosed with a clinically defined progressive dysexecutive syndrome with 18 F-fluorodeoxyglucose-positron emission tomography and Alzheimer's disease biomarkers available. Sixty-two per cent of participants were female with a mean of 15.2 years of education. The mean age of reported symptom onset was 53.8 years while the mean age at diagnosis was 57.2 years. Participants and informants commonly referred to initial cognitive symptoms as 'memory problems' but upon further inquiry described problems with core executive functions of working memory, cognitive flexibility and cognitive inhibitory control. Multi-domain cognitive impairment was evident in neuropsychological testing with executive dysfunction most consistently affected. The frontal and parietal regions which overlap with working memory networks consistently demonstrated hypometabolism on positron emission tomography. Genetic testing for autosomal dominant genes was negative in all eight participants tested and at least one APOE ε 4 allele was present in 14/26 participants tested. EEG was abnormal in 14/17 cases with 13 described as diffuse slowing. Furthermore, CSF or neuroimaging biomarkers were consistent with Alzheimer's disease pathophysiology, although CSF p-tau was normal in 24% of cases. Fifteen of the executive predominate participants enrolled in research neuroimaging protocols and were compared to amnestic ( n  = 110), visual ( n  = 18) and language ( n  = 7) predominate clinical phenotypes of Alzheimer's disease. This revealed a consistent pattern of hypometabolism in parieto-frontal brain regions supporting executive functions with relative sparing of the medial temporal lobe (versus amnestic phenotype), occipital (versus visual phenotype) and left temporal (versus language phenotype). We propose that this progressive dysexecutive syndrome should be recognized as a distinct clinical phenotype disambiguated from behavioural presentations and not linked specifically to the frontal lobe or a particular anatomic substrate without further study. This clinical presentation can be due to Alzheimer's disease but is likely not specific for any single aetiology. Diagnostic criteria are proposed to facilitate additional research into this understudied clinical presentation., (© The Author(s) (2020). Published by Oxford University Press on behalf of the Guarantors of Brain.)

Large phenotypically diverse research cohorts with both amyloid and tau PET have only recently come into existence. Our objective was to determine relationships between the bivariate distribution of amyloid-β and tau on PET and established clinical syndromes that are relevant to cognitive ageing and dementia. All individuals in this study were enrolled in the Mayo Clinic Study of Aging, a longitudinal population-based study of cognitive ageing, or the Mayo Alzheimer Disease Research Center, a longitudinal study of individuals recruited from clinical practice. We studied 1343 participants who had amyloid PET and tau PET from 2 April 2015 to 3 May 2019, and met criteria for membership in one of five clinical diagnostic groups: cognitively unimpaired, mild cognitive impairment, frontotemporal dementia, probable dementia with Lewy bodies, and Alzheimer clinical syndrome. We examined these clinical groups in relation to the bivariate distribution of amyloid and tau PET values. Individuals were grouped into amyloid (A)/tau (T) quadrants based on previously established abnormality cut points of standardized uptake value ratio 1.48 (A) and 1.33 (T). Individual participants largely fell into one of three amyloid/tau quadrants: low amyloid and low tau (A-T-), high amyloid and low tau (A+T-), or high amyloid and high tau (A+T+). Seventy per cent of cognitively unimpaired and 74% of FTD participants fell into the A-T- quadrant. Participants with mild cognitive impairment spanned the A-T- (42%), A+T- (28%), and A+T+ (27%) quadrants. Probable dementia with Lewy body participants spanned the A-T- (38%) and A+T- (44%) quadrants. Most (89%) participants with Alzheimer clinical syndrome fell into the A+T+ quadrant. These data support several conclusions. First, among 1343 participants, abnormal tau PET rarely occurred in the absence of abnormal amyloid PET, but the reverse was common. Thus, with rare exceptions, amyloidosis appears to be required for high levels of 3R/4R tau deposition. Second, abnormal amyloid PET is compatible with normal cognition but highly abnormal tau PET is not. These two conclusions support a dynamic biomarker model in which Alzheimer's disease is characterized first by the appearance of amyloidosis and later by tauopathy, with tauopathy being the proteinopathy associated with clinical symptoms. Third, bivariate amyloid and tau PET relationships differed across clinical groups and thus have a role for clarifying the aetiologies underlying neurocognitive clinical syndromes., (© The Author(s) (2019). Published by Oxford University Press on behalf of the Guarantors of Brain.)

Although white matter hyperintensities have traditionally been viewed as a marker of vascular disease, recent pathology studies have found an association between white matter hyperintensities and Alzheimer's disease pathologies. The objectives of this study were to investigate the topographic patterns of white matter hyperintensities associated with Alzheimer's disease biomarkers measured using PET. From the population-based Mayo Clinic Study of Aging, 434 participants without dementia (55% male) with FLAIR and gradient recall echo MRI, tau-PET (AV-1451) and amyloid-PET scans were identified. A subset had cerebral microbleeds detected on T2* gradient recall echo scans. White matter hyperintensities were semi-automatically segmented using FLAIR MRI in participant space and normalized to a custom template. We used statistical parametric mapping 12-based, voxel-wise, multiple-regression analyses to detect white matter hyperintense regions associated with Alzheimer's biomarkers (global amyloid from amyloid-PET and meta-regions of interest tau uptake from tau-PET) after adjusting for age, sex and hypertension. For amyloid associations, we additionally adjusted for tau and vice versa. Topographic patterns of amyloid-associated white matter hyperintensities included periventricular white matter hyperintensities (frontal and parietal lobes). White matter hyperintense volumes in the detected topographic pattern correlated strongly with lobar cerebral microbleeds (P < 0.001, age and sex adjusted Cohen's d = 0.703). In contrast, there were no white matter hyperintense regions significantly associated with increased tau burden using voxel-based analysis or region-specific analysis. Among non-demented elderly, amyloid load correlated with a topographic pattern of white matter hyperintensities. Further, the amyloid-associated, white matter hyperintense regions strongly correlated with lobar cerebral microbleeds suggesting that cerebral amyloid angiopathy contributes to the relationship between amyloid and white matter hyperintensities. The study did not support an association between increased tau burden and white matter hyperintense burden., (© The Author(s) (2019). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Research into cognitive resilience imaging markers may help determine the clinical significance of Alzheimer's disease pathology among older adults over 80 years (80+). In this study, we aimed to identify a fluorodeoxyglucose (FDG)-PET based imaging marker of cognitive resilience. We identified 457 participants ≥ 80 years old (357 cognitively unimpaired, 118 cognitively impaired at baseline, mean age of 83.5 ± 3.2 years) from the population-based Mayo Clinic Study of Aging (MCSA) with baseline MRI, Pittsburgh compound B-PET and FDG-PET scans and neuropsychological evaluation. We identified a subset of 'resilient' participants (cognitively stable 80+, n = 192) who maintained normal cognition for an average of 5 years (2-10 years). Global PIB ratio, FDG-PET ratio and cortical thickness from Alzheimer's disease signature regions were used as Alzheimer's disease imaging biomarker outcomes and global cognitive z-score was used as a cognitive outcome. First, using voxel-wise multiple regression analysis, we identified the metabolic areas underlying cognitive resilience in cognitively stable 80+ participants, which we call the 'resilience signature'. Second, using multivariate linear regression models, we evaluated the association of risk and protective factors with the resilience signature and its added value for predicting global cognition beyond established Alzheimer's disease imaging biomarkers in the full 80+ sample. Third, we evaluated the utility of the resilience signature in conjunction with amyloidosis in predicting longitudinal cognition using linear mixed effect models. Lastly, we assessed the utility of the resilience signature in an independent cohort using ADNI (n = 358, baseline mean age of 80 ± 3.8). Our main findings were: (i) FDG-PET uptake in the bilateral anterior cingulate cortex and anterior temporal pole was associated with baseline global cognition in cognitively stable 80+ (the resilience signature); (ii) established Alzheimer's disease imaging biomarkers did not predict baseline global cognition in this subset of participants; (iii) in the full MCSA 80+ and ADNI cohorts, amyloid burden and FDG-PET in the resilience signature were the stronger predictors of baseline global cognition; (iv) sex and systemic vascular health predicted FDG-PET in the resilience signature, suggesting vascular health maintenance as a potential pathway to preserve the metabolism of these areas; and (v) the resilience signature provided significant information about global longitudinal cognitive change even when considering amyloid status in both the MCSA and ADNI cohorts. The FDG-PET resilience signature may be able to provide important information in conjunction with other Alzheimer's disease biomarkers for the determination of clinical prognosis. It may also facilitate identification of disease targeting modifiable risk factors such as vascular health maintenance., (© The Author(s) (2019). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

As more biomarkers for Alzheimer's disease and age-related brain conditions become available, more sophisticated analytic approaches are needed to take full advantage of the information they convey. Most work has been done using categorical approaches but the joint relationships of tau PET, amyloid PET and cortical thickness in their continuous distributions to cognition have been under-explored. We evaluated non-demented subjects over age 50 years in the Mayo Clinic Study of Aging, 2037 of whom had undergone 3 T MRI scan, 985 amyloid PET scan with 11C-Pittsburgh compound B (PIB) and MRI, and 577 PIB-PET, 18F-AV1451 flortaucipir PET and MRI. Participants received a nine-test cognitive battery. Three test scores (logical memory delayed recall, visual reproduction delayed recall and auditory verbal learning test delayed recall) were used to generate a memory composite z-score. We used Gradient Boosting Machine models to analyse the relationship between regional cortical thickness, flortaucipir PET signal, PIB-PET signal and memory z-scores. Age, education, sex and number of test exposures were included in the model as covariates. In this population-based study of non-demented subjects, most of the associations between biomarkers and memory z-scores accrued after 70 years of age. Entorhinal cortex exhibited the strongest associations between biomarkers and memory z-scores. Other temporal regions showed similar but attenuated associations, and non-temporal regions had negligible associations between memory z-scores and biomarkers. Entorhinal flortaucipir PET signal, PIB-PET signal and entorhinal cortical thickness were independently and additively associated with declining memory z-scores. In contrast to global PIB-PET signal where only very high amyloid-β levels were associated low memory z-scores, entorhinal flortaucipir PET signal just above background levels was associated with low memory z-scores. The lowest memory z-scores occurred with the confluence of elevated entorhinal flortaucipir PET signal and lower entorhinal cortical thickness., (© The Author(s) (2019). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

See Hansson and Mormino (doi:10.1093/brain/awy065) for a scientific commentary on this article.Our objective was to compare different whole-brain and region-specific measurements of within-person change on serial tau PET and evaluate its utility for clinical trials. We studied 126 individuals: 59 cognitively unimpaired with normal amyloid, 37 cognitively unimpaired with abnormal amyloid, and 30 cognitively impaired with an amnestic phenotype and abnormal amyloid. All had baseline amyloid PET and two tau PET, MRI, and clinical assessments. We compared the topography across all cortical regions of interest of tau PET accumulation rates and the rates of four different whole-brain or region-specific meta-regions of interest among the three clinical groups. We computed sample size estimates for change in tau PET, cortical volume, and memory/mental status indices for use as outcome measures in clinical trials. The cognitively unimpaired normal amyloid group had no observable tau accumulation throughout the brain. Tau accumulation rates in cognitively unimpaired abnormal amyloid were low [0.006 standardized uptake value ratio (SUVR), 0.5%, per year] but greater than rates in the cognitively unimpaired normal amyloid group in the basal and mid-temporal, retrosplenial, posterior cingulate, and entorhinal regions of interest. Thus, the earliest elevation in accumulation rates was widespread and not confined to the entorhinal cortex. Tau accumulation rates in the cognitively impaired abnormal amyloid group were 0.053 SUVR (3%) per year and greater than rates in cognitively unimpaired abnormal amyloid in all cortical areas except medial temporal. Rates of accumulation in the four meta-regions of interest differed but only slightly from one another. Among all tau PET meta-regions of interest, sample size estimates were smallest for a temporal lobe composite within cognitively unimpaired abnormal amyloid and for the late Alzheimer's disease meta-region of interest within cognitively impaired abnormal amyloid. The ordering of the sample size estimates by outcome measure was MRI < tau PET < cognitive measures. At a group-wise level, observable rates of short-term serial tau accumulation were only seen in the presence of abnormal amyloid. As disease progressed to clinically symptomatic stages (cognitively impaired abnormal amyloid), observable rates of tau accumulation were seen uniformly throughout the brain providing evidence that tau does not accumulate in one area at a time or in start-stop, stepwise sequence. The information captured by rate measures in different meta-regions of interest, even those with little topographic overlap, was similar. The implication is that rate measurements from simple meta-regions of interest, without the need for Braak-like staging, may be sufficient to capture progressive within-person accumulation of pathologic tau. Tau PET SUVR measures should be an efficient outcome measure in disease-modifying clinical trials.

See Gordon (doi:10.1093/brain/awy052) for a scientific commentary on this article.Predicting underlying pathology based on clinical presentation has historically proven difficult, especially in older cohorts. Age-related hippocampal sclerosis may account for a significant proportion of elderly participants with amnestic dementia. Advances in molecular neuroimaging have allowed for detailed biomarker-based phenotyping, but in the absence of antemortem markers of hippocampal sclerosis, cases of mixed pathology remain problematic. We evaluated the utility of 18F-FDG-PET to differentiate flortaucipir tau PET negative from flortaucipir positive amnestic mild cognitive impairment and dementia and used an autopsy confirmed cohort to test the hypothesis that hippocampal sclerosis might account for the observed pattern. We identified impaired participants (Clinical Dementia Rating > 0) with amnestic presentations ≥ 75 years who had MRI and PET imaging with 18F-FDG (glucose metabolism), Pittsburgh compound B (amyloid) and flortaucipir (tau) performed within a year of cognitive assessment. These were stratified into amyloid positive/negative and tau positive/negative according to the A/T/N classification scheme. Our sample included 15 amyloid and tau-positive participants, and nine tau-negative participants (five of whom were amyloid-positive). For the autopsy cohort, sequential cases with antemortem 18F-FDG-PET were screened and those with TDP-43-negative Alzheimer's disease (10 cases) and TDP-43-positive hippocampal sclerosis (eight cases) were included. We compared each group to controls and to each other in a voxel-based analysis, and supplemented this with a region of interest-based analysis comparing medial to inferior temporal metabolism. Tau-positive and negative cases did not differ on neuropsychological testing or structural magnetic resonance biomarkers. Tau-negative cases had focal medial temporal and posterior cingulate/retrosplenial hypometabolism regardless of amyloid status, whereas tau-positive cases had additional lateral parietal and inferior temporal involvement. The inferior/medial temporal metabolism ratio was significantly different between the groups with the tau-negative group having a higher ratio. In the autopsy series, hippocampal sclerosis cases had greater medial temporal hypometabolism than Alzheimer's disease cases, who had more parietal and lateral/inferior temporal hypometabolism. Again, the ratio between temporal regions of interest differed significantly between groups. Two of the tau-negative patients, both of whom had an elevated inferior/medial temporal ratio, came to autopsy during the study and were found to have hippocampal sclerosis. Our finding that tau-negative amnestic mild cognitive impairment and dementia is associated with focal medial temporal and posterior cingulate hypometabolism extends prior reports in amyloid-negative cases. The inferior/medial temporal metabolism ratio can help identify tau-negative cases of amnestic dementia and may serve as a biomarker for hippocampal sclerosis.

See Herholz (doi:10.1093/brain/awx340) for a scientific commentary on this article.Autopsy data have proposed that a topographical pattern of tauopathy occurs in the brain with the development of dementia due to Alzheimer's disease. We evaluated the findings of tau-PET to better understand neurofibrillary tangle development as it is seen in cognitively unimpaired and impaired individuals. The evolution of Alzheimer's disease tauopathy in cognitively unimpaired individuals needs to be examined to better understand disease pathogenesis. Tau-PET was performed in 86 cognitively impaired individuals who all had abnormal amyloid levels and 601 cognitively unimpaired individuals. Tau-PET findings were assessed for relationships with clinical diagnosis, age, and regional uptake patterns relative to Braak stage. Regional and voxel-wise analyses were performed. Topographical findings from tau-PET were characterized using hierarchical clustering and clinical characteristic-based subcategorization. In older cognitively unimpaired individuals (≥50 years), widespread, age-related elevated tau signal was seen among those with normal or abnormal amyloid status as compared to younger cognitively unimpaired individuals (30-49 years). More frequent regional tau signal elevation throughout the brain was seen in cognitively unimpaired individuals with abnormal versus normal amyloid. Elevated tau signal was seen in regions that are considered high Braak Stage in cognitively unimpaired and cognitively impaired individuals. Hierarchical clustering and clinical characteristic-based categorizations both showed different patterns of tau signal between groups such as greater tau signal in frontal regions in younger onset Alzheimer's disease dementia participants (most of whom had a dysexecutive clinical presentation). Tau-PET signal increases modestly with age throughout the brain in cognitively unimpaired individuals and elevated tau is seen more often when amyloid brain accumulation is present. Tau signal patterns in cognitively unimpaired correspond to early Braak stage but also suggest tangle involvement in extra-medial temporal and extra-temporal regions that are considered more advanced in the Braak scheme even when amyloid negative. Our findings also suggest the possibility of widespread development of early tangle pathology rather than a pattern defined exclusively by adjacent, region-to-region spread, prior to onset of clinical symptoms. Distinct patterns of neurofibrillary tangle deposition in younger-onset Alzheimer's disease dementia versus older-onset Alzheimer's disease dementia provide evidence for variability in regional tangle deposition patterns and demonstrate that different disease phenotypes have different patterns of tauopathy. Pathological correlation with imaging is needed to assess the implications of these observations., (© The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Alzheimer's disease pathology frequently coexists with Lewy body disease at autopsy in patients with probable dementia with Lewy bodies. More than half of patients with probable dementia with Lewy bodies have high amyloid-β deposition as measured with 11 C-Pittsburgh compound B binding on positron emission tomography. Biomarkers of amyloid-β deposition precede neurodegeneration on magnetic resonance imaging during the progression of Alzheimer's disease, but little is known about how amyloid-β deposition relates to longitudinal progression of atrophy in patients with probable dementia with Lewy bodies. We investigated the associations between baseline 11 C-Pittsburgh compound B binding on positron emission tomography and the longitudinal rates of grey matter atrophy in a cohort of clinically diagnosed patients with dementia with Lewy bodies (n = 20), who were consecutively recruited to the Mayo Clinic Alzheimer's Disease Research Centre. All patients underwent 11 C-Pittsburgh compound B positron emission tomography and magnetic resonance imaging examinations at baseline. Follow-up magnetic resonance imaging was performed after a mean (standard deviation) interval of 2.5 (1.1) years. Regional grey matter loss was determined on three-dimensional T 1 -weighted magnetic resonance imaging with the tensor-based morphometry-symmetric normalization technique. Linear regression was performed between baseline 11 C-Pittsburgh compound B standard unit value ratio and longitudinal change in regional grey matter volumes from an in-house modified atlas. We identified significant associations between greater baseline 11 C-Pittsburgh compound B standard unit value ratio and greater grey matter loss over time in the posterior cingulate gyrus, lateral and medial temporal lobe, and occipital lobe as well as caudate and putamen nuclei, after adjusting for age (P < 0.05). Greater baseline 11 C-Pittsburgh compound B standard unit value ratio was also associated with greater ventricular expansion rates (P < 0.01) and greater worsening over time in Clinical Dementia Rating Scale, sum of boxes (P = 0.02). In conclusion, in patients with probable dementia with Lewy bodies, higher amyloid-β deposition at baseline is predictive of faster neurodegeneration in the cortex and also in the striatum. This distribution is suggestive of possible interactions among amyloid-β, tau and α-synuclein aggregates, which needs further investigation. Furthermore, higher amyloid-β deposition at baseline predicts a faster clinical decline over time in patients with probable dementia with Lewy bodies., (© The Author (2016). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Complex biological systems are organized across various spatiotemporal scales with particular scientific disciplines dedicated to the study of each scale (e.g. genetics, molecular biology and cognitive neuroscience). When considering disease pathophysiology, one must contemplate the scale at which the disease process is being observed and how these processes impact other levels of organization. Historically Alzheimer's disease has been viewed as a disease of abnormally aggregated proteins by pathologists and molecular biologists and a disease of clinical symptoms by neurologists and psychologists. Bridging the divide between these scales has been elusive, but the study of brain networks appears to be a pivotal inroad to accomplish this task. In this study, we were guided by an emerging systems-based conceptualization of Alzheimer's disease and investigated changes in brain networks across the disease spectrum. The default mode network has distinct subsystems with unique functional-anatomic connectivity, cognitive associations, and responses to Alzheimer's pathophysiology. These distinctions provide a window into the systems-level pathophysiology of Alzheimer's disease. Using clinical phenotyping, metadata, and multimodal neuroimaging data from the Alzheimer's Disease Neuroimaging Initiative, we characterized the pattern of default mode network subsystem connectivity changes across the entire disease spectrum (n = 128). The two main findings of this paper are (i) the posterior default mode network fails before measurable amyloid plaques and appears to initiate a connectivity cascade that continues throughout the disease spectrum; and (ii) high connectivity between the posterior default mode network and hubs of high connectivity (many located in the frontal lobe) is associated with amyloid accumulation. These findings support a system model best characterized by a cascading network failure--analogous to cascading failures seen in power grids triggered by local overloads proliferating to downstream nodes eventually leading to widespread power outages, or systems failures. The failure begins in the posterior default mode network, which then shifts processing burden to other systems containing prominent connectivity hubs. This model predicts a connectivity 'overload' that precedes structural and functional declines and recasts the interpretation of high connectivity from that of a positive compensatory phenomenon to that of a load-shifting process transiently serving a compensatory role. It is unknown whether this systems-level pathophysiology is the inciting event driving downstream molecular events related to synaptic activity embedded in these systems. Possible interpretations include that the molecular-level events drive the network failure, a pathological interaction between the network-level and the molecular-level, or other upstream factors are driving both., (© The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain.)

Acetylcholinesterase inhibitors are commonly used to treat patients with dementia with Lewy bodies. Hippocampal atrophy on magnetic resonance imaging and amyloid-β load on positron emission tomography are associated with the Alzheimer's disease-related pathology in patients with dementia with Lewy bodies. To date, few studies have investigated imaging markers that predict treatment response in patients with dementia with Lewy bodies. Our objective was to determine whether imaging markers of Alzheimer's disease-related pathology such as hippocampal volume, brain amyloid-β load on (11)C Pittsburgh compound B positron emission tomography predict treatment response to acetylcholinesterase inhibitors in patients with dementia with Lewy bodies. We performed a retrospective analysis on consecutive treatment-naive patients with dementia with Lewy bodies (n = 54) from the Mayo Clinic Alzheimer's Disease Research Centre who subsequently received acetylcholinesterase inhibitors and underwent magnetic resonance imaging with hippocampal volumetry. Baseline and follow-up assessments were obtained with the Mattis Dementia Rating Scale. Subjects were divided into three groups (reliable improvement, stable or reliable decline) using Dementia Rating Scale reliable change indices determined previously. Associations between hippocampal volumes and treatment response were tested with analysis of covariance adjusting for baseline Dementia Rating Scale, age, gender, magnetic resonance field strength and Dementia Rating Scale interval. Seven subjects underwent (11)C Pittsburgh compound B imaging within 12 weeks of magnetic resonance imaging. Global cortical (11)C Pittsburgh compound B retention (scaled to cerebellar retention) was calculated in these patients. Using a conservative psychometric method of assessing treatment response, there were 12 patients with reliable decline, 29 stable cases and 13 patients with reliable improvement. The improvers had significantly larger hippocampi than those that declined (P = 0.02) and the stable (P = 0.04) group. An exploratory analysis demonstrated larger grey matter volumes in the temporal and parietal lobes in improvers compared with those who declined (P < 0.05). The two patients who had a positive (11)C Pittsburgh compound B positron emission tomography scan declined and those who had a negative (11)C Pittsburgh compound B positron emission tomography scan improved or were stable after treatment. Patients with dementia with Lewy bodies who do not have the imaging features of coexistent Alzheimer's disease-related pathology are more likely to cognitively improve with acetylcholinesterase inhibitor treatment.