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.

Patients with Alzheimer's disease (AD) and dementia with Lewy bodies (DLB) frequently demonstrate coexistent AD neuropathological change (ADNC) and Lewy body pathology (LBP) at autopsy. We investigated the effects of ADNC and LBP on the clinical presentation of these patients.

Measurement of amyloid beta (Aβ40 and Aβ42) and tau (phosphorylated tau [p-tau] and total tau [t-tau]) in cerebrospinal fluid (CSF) can be utilized to differentiate clinical and preclinical Alzheimer's disease dementia (AD) from other neurodegenerative processes.

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.

Selective vulnerability of different brain regions is seen in many neurodegenerative disorders. The hippocampus and cortex are selectively vulnerable in Alzheimer's disease (AD), however the degree of involvement of the different brain regions differs among patients. We classified corticolimbic patterns of neurofibrillary tangles in postmortem tissue to capture extreme and representative phenotypes. We combined bulk RNA sequencing with digital pathology to examine hippocampal vulnerability in AD. We identified hippocampal gene expression changes associated with hippocampal vulnerability and used machine learning to identify genes that were associated with AD neuropathology, including SERPINA5, RYBP, SLC38A2, FEM1B, and PYDC1. Further histologic and biochemical analyses suggested SERPINA5 expression is associated with tau expression in the brain. Our study highlights the importance of embracing heterogeneity of the human brain in disease to identify disease-relevant gene expression.

Since tau PET tracers were introduced, investigators have quantified them using a wide variety of automated methods. As longitudinal cohort studies acquire second and third time points of serial within-person tau PET data, determining the best pipeline to measure change has become crucial. We compared a total of 415 different quantification methods (each a combination of multiple options) according to their effects on a) differences in annual SUVR change between clinical groups, and b) longitudinal measurement repeatability as measured by the error term from a linear mixed-effects model. Our comparisons used MRI and Flortaucipir scans of 97 Mayo Clinic study participants who clinically either: a) were cognitively unimpaired, or b) had cognitive impairments that were consistent with Alzheimer's disease pathology. Tested methods included cross-sectional and longitudinal variants of two overarching pipelines (FreeSurfer 6.0, and an in-house pipeline based on SPM12), three choices of target region (entorhinal, inferior temporal, and a temporal lobe meta-ROI), five types of partial volume correction (PVC) (none, two-compartment, three-compartment, geometric transfer matrix (GTM), and a tau-specific GTM variant), seven choices of reference region (cerebellar crus, cerebellar gray matter, whole cerebellum, pons, supratentorial white matter, eroded supratentorial WM, and a composite of eroded supratentorial WM, pons, and whole cerebellum), two choices of region masking (GM or GM and WM), and two choices of statistic (voxel-wise mean vs. median). Our strongest findings were: 1) larger temporal-lobe target regions greatly outperformed entorhinal cortex (median sample size estimates based on a hypothetical clinical trial were 520-526 vs. 1740); 2) longitudinal processing pipelines outperformed cross-sectional pipelines (median sample size estimates were 483 vs. 572); and 3) reference regions including supratentorial WM outperformed traditional cerebellar and pontine options (median sample size estimates were 370 vs. 559). Altogether, our results favored longitudinally SUVR methods and a temporal-lobe meta-ROI that includes adjacent (juxtacortical) WM, a composite reference region (eroded supratentorial WM + pons + whole cerebellum), 2-class voxel-based PVC, and median statistics.

Advances in ultrasensitive detection of phosphorylated tau (p-tau) in plasma has enabled the use of blood tests to measure Alzheimer's disease (AD) biomarker changes. Examination of postmortem brains of participants with antemortem plasma p-tau levels remains critical to understanding comorbid and AD-specific contribution to these biomarker changes.

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.

Whether a relationship exists between cerebrovascular disease and Alzheimer's disease has been a source of controversy. Evaluation of the temporal progression of imaging biomarkers of these disease processes may inform mechanistic associations. We investigate the relationship of disease trajectories of cerebrovascular disease (white matter hyperintensity, WMH, and fractional anisotropy, FA) and Alzheimer's disease (amyloid and tau PET) biomarkers in 2406 Mayo Clinic Study of Aging and Mayo Alzheimer's Disease Research Center participants using accelerated failure time models. The model assumes a common pattern of progression for each biomarker that is shifted earlier or later in time for each individual and represented by a per participant age adjustment. An individual's amyloid and tau PET adjustments show very weak temporal association with WMH and FA adjustments (R = -0.07 to 0.07); early/late amyloid or tau timing explains <1% of the variation in WMH and FA adjustment. Earlier onset of amyloid is associated with earlier onset of tau (R = 0.57, R2 = 32%). These findings support a strong mechanistic relationship between amyloid and tau aggregation, but not between WMH or FA and amyloid or tau PET.

Cellular senescence has been identified as a pathological mechanism linked to tau and amyloid beta (Aβ) accumulation in mouse models of Alzheimer's disease (AD). Clearance of senescent cells using the senolytic compounds dasatinib (D) and quercetin (Q) reduced neuropathological burden and improved clinically relevant outcomes in the mice. Herein, we conducted a vanguard open-label clinical trial of senolytic therapy for AD with the primary aim of evaluating central nervous system (CNS) penetrance, as well as exploratory data collection relevant to safety, feasibility, and efficacy. Participants with early-stage symptomatic AD were enrolled in an open-label, 12-week pilot study of intermittent orally-delivered D+Q. CNS penetrance was assessed by evaluating drug levels in cerebrospinal fluid (CSF) using high performance liquid chromatography with tandem mass spectrometry. Safety was continuously monitored with adverse event reporting, vitals, and laboratory work. Cognition, neuroimaging, and plasma and CSF biomarkers were assessed at baseline and post-treatment. Five participants (mean age: 76±5 years; 40% female) completed the trial. The treatment increased D and Q levels in the blood of all participants ranging from 12.7 to 73.5 ng/ml for D and 3.29-26.30 ng/ml for Q. D levels were detected in the CSF of four participants ranging from 0.281 to 0.536 ng/ml (t(4)=3.123, p=0.035); Q was not detected. Treatment was well-tolerated with no early discontinuation and six mild to moderate adverse events occurring across the study. Cognitive and neuroimaging endpoints did not significantly differ from baseline to post-treatment. CNS levels of IL-6 and GFAP increased from baseline to post-treatment (t(4)=3.913, p=008 and t(4)=3.354, p=0.028, respectively) concomitant with decreased levels of several cytokines and chemokines associated with senescence, and a trend toward higher levels of Aβ42 (t(4)=-2.338, p=0.079). Collectively the data indicate the CNS penetrance of D and provide preliminary support for the safety, tolerability, and feasibility of the intervention and suggest that astrocytes and Aβ may be particularly responsive to the treatment. While early results are promising, fully powered, placebo-controlled studies are needed to evaluate the potential of AD modification with the novel approach of targeting cellular senescence.

Our primary objective was to compare the performance of unaccelerated vs. accelerated structural MRI for measuring disease progression using serial scans in Alzheimer's disease (AD).

Pathogenic mutations in PSEN1 are known to cause familial early-onset Alzheimer's disease (EOAD) but common variants in PSEN1 have not been found to strongly influence late-onset AD (LOAD). The association of rare variants in PSEN1 with LOAD-related endophenotypes has received little attention. In this study, we performed a rare variant association analysis of PSEN1 with quantitative biomarkers of LOAD using whole genome sequencing (WGS) by integrating bioinformatics and imaging informatics.

Dementia with Lewy bodies (DLB) is the second leading cause of neurodegenerative dementia in the elderly and is clinically characterized by the presence of cognitive decline, parkinsonism, REM sleep behavior disorder, and visual hallucinations.(1,2) At autopsy, α-synuclein-positive Lewy-related pathology is observed throughout the brain. Concomitant Alzheimer disease-related pathology including amyloid plaques and, to a lesser degree, neurofibrillary tangles are often present.(2) The clinical characteristics of DLB share overlapping features with Alzheimer disease dementia (AD) and Parkinson disease (PD). A recent genetic association study examining known hits from PD and AD identified variants at both the α-synuclein (SNCA) and APOE loci as influencing the individual risk to DLB.(3) These findings would suggest that DLB may be a distinct disease with shared genetic risk factors with PD and AD.

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.

We recently demonstrated that the frequencies of biomarker groups defined by the presence or absence of both amyloidosis (A+) and neurodegeneration (N+) changed dramatically by age in cognitively non-impaired subjects. Our present objectives were to assess the consequences of defining neurodegeneration in five different ways on the frequency of subjects classified as N+, on the demographic associations with N+, and on amyloidosis and neurodegeneration (A/N) biomarker group frequencies by age. This was a largely cross-sectional observational study of 1331 cognitively non-impaired subjects aged 50-89 drawn from a population-based study of cognitive ageing. We assessed demographic associations with N+, and A/N biomarker group frequencies by age where A+ was defined by amyloid PET and N+ was defined in five different ways: (i) abnormal adjusted hippocampal volume alone; (ii) abnormal Alzheimer's disease signature cortical thickness alone; (iii) abnormal fluorodeoxyglucose positron emission tomography alone; (iv) abnormal adjusted hippocampal volume or abnormal fluorodeoxyglucose positron emission tomography; and (v) abnormal Alzheimer's disease signature cortical thickness or abnormal fluorodeoxyglucose positron emission tomography. For each N+ definition, participants were assigned to one of four biomarker groups; A-N-, A+N-, A-N+, or A+N+. The three continuous individual neurodegeneration measures were moderately correlated (rs = 0.42 to 0.54) but when classified as normal or abnormal had only weak agreement (κ = 0.20 to 0.29). The adjusted hippocampal volume alone definition classified the fewest subjects as N+ while the Alzheimer's disease signature cortical thickness or abnormal fluorodeoxyglucose positron emission tomography definition classified the most as N+. Across all N+ definitions, N+ subjects tended to be older, more often male and APOE4 carriers, and performed less well on functional status and learning and memory than N- subjects. For all definitions of neurodegeneration, (i) the frequency of A-N- was 100% at age 50 and declined monotonically thereafter; (ii) the frequency of A+N- increased from age 50 to a maximum in the mid-70s and declined thereafter; and3 (iii) the frequency of A-N+ (suspected non-Alzheimer's pathophysiology) and of A+N+ increased monotonically beginning in the mid-50s and mid-60s, respectively. Overall, different neurodegeneration measures provide similar but not completely redundant information. Despite quantitative differences, the overall qualitative pattern of the A-N-, A+N-, A-N+, and A+N+ biomarker group frequency curves by age were similar across the five different definitions of neurodegeneration. We conclude that grouping subjects by amyloidosis and neurodegeneration status (normal/abnormal) is robust to different imaging definitions of neurodegeneration and thus is a useful way for investigators throughout the field to communicate in a common classification framework.

The genetics underlying posterior cortical atrophy (PCA), typically a rare variant of Alzheimer's disease (AD), remain uncertain.

The clinical and pathological phenotypes of Dementia with Lewy Bodies (DLB) and Alzheimer's disease (AD) often overlap. We examined whether plasma lipids differed among individuals with autopsy-confirmed Lewy Body pathology or AD pathology.

The 12 genome-wide association studies (GWAS) published to-date for late-onset Alzheimer's disease (LOAD) have identified over 40 candidate LOAD risk modifiers, in addition to apolipoprotein (APOE) ε4. A few of these novel LOAD candidate genes, namely BIN1, CLU, CR1, EXOC3L2 and PICALM, have shown consistent replication, and are thus credible LOAD susceptibility genes. To evaluate other promising LOAD candidate genes, we have added data from our large, case-control series (n=5,043) to meta-analyses of all published follow-up case-control association studies for six LOAD candidate genes that have shown significant association across multiple studies (TNK1, GAB2, LOC651924, GWA_14q32.13, PGBD1 and GALP) and for an additional nine previously suggested candidate genes. Meta-analyses remained significant at three loci after addition of our data: GAB2 (OR=0.78, p=0.007), LOC651924 (OR=0.91, p=0.01) and TNK1 (OR=0.92, p=0.02). Breslow-Day tests revealed significant heterogeneity between studies for GAB2 (p<0.0001) and GWA_14q32.13 (p=0.006). We have also provided suggestive evidence that PGBD1 (p=0.04) and EBF3 (p=0.03) are associated with age-at-onset of LOAD. Finally, we tested for interactions between these 15 genes, APOE ε4 and the five novel LOAD genes BIN1, CLU, CR1, EXOC3L2 and PICALM but none were significant after correction for multiple testing. Overall, this large, independent follow-up study for 15 of the top LOAD candidate genes provides support for GAB2 and LOC651924 (6q24.1) as risk modifiers of LOAD and novel associations between PGBD1 and EBF3 with age-at-onset.

KIBRA single nucleotide polymorphism (SNP) rs17070145 was identified in a genome-wide association study (GWAS) of memory performance, with some but not all follow-up studies confirming association of its T allele with enhanced memory. This allele was associated with reduced Alzheimer's disease (AD) risk in 1 study, which also found overexpression of KIBRA in memory-related brain regions of AD. We genotyped rs17070145 and 14 additional SNPs in 2571 late onset Alzheimer's disease (LOAD) patients vs. 2842 controls, including African-Americans. We found significantly reduced risk for rs17070145 T allele in the older African-American subjects (p = 0.007) and a suggestive effect in the older Caucasian series. Meta-analysis of this allele in > 8000 subjects from our and published series showed a suggestive protective effect (p = 0.07). Analysis of episodic memory in control subjects did not identify associations with rs17070145, though other SNPs showed significant associations in 1 series. KIBRA showed evidence of overexpression in the AD temporal cortex (p = 0.06) but not cerebellum. These results suggest a modest role for KIBRA as a cognition and AD risk gene, and also highlight the multifactorial complexity of its genetic associations.

The aim of this study was to compare patterns of cerebral atrophy on MRI, and neurochemistry on magnetic resonance spectroscopy (MRS), in patients with posterior cortical atrophy (PCA) and typical Alzheimer's disease (AD). Voxel-based morphometry was used to assess grey matter atrophy in 38 patients with PCA, 38 patients with typical AD, and 38 controls. Clinical data was assessed in all PCA patients. Single voxel (1)H MRS located in the posterior cingulate was analyzed in a subset of patients with PCA, typical AD, and control subjects. PCA showed a pattern of atrophy affecting occipital, parietal and posterior temporal lobes, compared to controls. The pattern was bilateral, but more severe on the right. Patients with PCA showed greater atrophy in the right visual association cortex than patients with typical AD, whereas those with AD showed greater atrophy in the left hippocampus than those with PCA. (1)H MRS suggested loss of neuronal integrity and glial activation in subjects with PCA and typical AD. The differing patterns of atrophy on MRI suggest that PCA should be considered a distinct entity from typical AD.