Alzheimer's disease: The influence of age on clinical heterogeneity through the human brain connectome

Assessing individual variability of the entorhinal subfields in health and disease

Investigating interindividual variability is a major field of interest in neuroscience. The entorhinal cortex (EC) is essential for memory and affected early in the progression of Alzheimer's disease (AD). We combined histology ground-truth data with ultrahigh-resolution 7T ex vivo MRI to analyze EC interindividual variability in 3D. Further, we characterized (1) entorhinal shape as a whole, (2) entorhinal subfield range and midpoints, and (3) subfield architectural location and tau burden derived from 3D probability maps. Our results indicated that EC shape varied but was not related to demographic or disease factors at this preclinical stage. The medial intermediate subfield showed the highest degree of location variability in the probability maps. However, individual subfields did not display the same level of variability across dimensions and outcome measure, each providing a different perspective. For example, the olfactory subfield showed low variability in midpoint location in the superior-inferior dimension but high variability in anterior-posterior, and the subfield entorhinal intermediate showed a large variability in volumetric measures but a low variability in location derived from the 3D probability maps. These findings suggest that interindividual variability within the entorhinal subfields requires a 3D approach incorporating multiple outcome measures. This study provides 3D probability maps of the individual entorhinal subfields and respective tau pathology in the preclinical stage (Braak I and II) of AD. These probability maps illustrate the subfield average and may serve as a checkpoint for future modeling.

Atrophy in behavioural variant frontotemporal dementia spans multiple large-scale prefrontal and temporal networks

The identification of a neurodegenerative disorder's distributed pattern of atrophy-or atrophy 'signature'-can lend insights into the cortical networks that degenerate in individuals with specific constellations of symptoms. In addition, this signature can be used as a biomarker to support early diagnoses and to potentially reveal pathological changes associated with said disorder. Here, we characterized the cortical atrophy signature of behavioural variant frontotemporal dementia (bvFTD). We used a data-driven approach to estimate cortical thickness using surface-based analyses in two independent, sporadic bvFTD samples (n = 30 and n = 71, total n = 101), using age- and gender-matched cognitively and behaviourally normal individuals. We found highly similar patterns of cortical atrophy across the two independent samples, supporting the reliability of our bvFTD signature. Next, we investigated whether our bvFTD signature targets specific large-scale cortical networks, as is the case for other neurodegenerative disorders. We specifically asked whether the bvFTD signature topographically overlaps with the salience network, as previous reports have suggested. We hypothesized that because phenotypic presentations of bvFTD are diverse, this would not be the case, and that the signature would cross canonical network boundaries. Consistent with our hypothesis, the bvFTD signature spanned rostral portions of multiple networks, including the default mode, limbic, frontoparietal control and salience networks. We then tested whether the signature comprised multiple anatomical subtypes, which themselves overlapped with specific networks. To explore this, we performed a hierarchical clustering analysis. This yielded three clusters, only one of which extensively overlapped with a canonical network (the limbic network). Taken together, these findings argue against the hypothesis that the salience network is preferentially affected in bvFTD, but rather suggest that-at least in patients who meet diagnostic criteria for the full-blown syndrome-neurodegeneration in bvFTD encompasses a distributed set of prefrontal, insular and anterior temporal nodes of multiple large-scale brain networks, in keeping with the phenotypic diversity of this disorder.

The Sporadic Early-onset Alzheimer's Disease Signature Of Atrophy: Preliminary Findings From The Longitudinal Early-onset Alzheimer's Disease Study (LEADS) Cohort

INTRODUCTION

Magnetic resonance imaging (MRI) research has advanced our understanding of neurodegeneration in sporadic early-onset Alzheimer's disease (EOAD) but studies include small samples, mostly amnestic EOAD, and have not focused on developing an MRI biomarker.

METHODS

We analyzed MRI scans to define the sporadic EOAD-signature atrophy in a small sample (n = 25) of Massachusetts General Hospital (MGH) EOAD patients, investigated its reproducibility in the large longitudinal early-onset Alzheimer's disease study (LEADS) sample (n = 211), and investigated the relationship of the magnitude of atrophy with cognitive impairment.

RESULTS

The EOAD-signature atrophy was replicated across the two cohorts, with prominent atrophy in the caudal lateral temporal cortex, inferior parietal lobule, and posterior cingulate and precuneus cortices, and with relative sparing of the medial temporal lobe. The magnitude of EOAD-signature atrophy was associated with the severity of cognitive impairment.

DISCUSSION

The EOAD-signature atrophy is a reliable and clinically valid biomarker of AD-related neurodegeneration that could be used in clinical trials for EOAD.

HIGHLIGHTS

We developed an early-onset Alzheimer's disease (EOAD)-signature of atrophy based on magnetic resonance imaging (MRI) scans. EOAD signature was robustly reproducible across two independent patient cohorts. EOAD signature included prominent atrophy in parietal and posterior temporal cortex. The EOAD-signature atrophy was associated with the severity of cognitive impairment. EOAD signature is a reliable and clinically valid biomarker of neurodegeneration.

PASSED: Brain atrophy in non-demented individuals in a long-term longitudinal study from two independent cohorts

Introduction

Alzheimer's disease (AD) is indicated by a decrease in amyloid beta 42 (Aβ42) level or the Aβ42/Aβ40 ratio, and by increased levels of Tau with phosphorylated threonine at position 181 (pTau181) in cerebrospinal fluid (CSF) years before the onset of clinical symptoms. However, once only pTau181 is increased, cognitive decline in individuals with subjective or mild cognitive impairment is slowed compared to individuals with AD. Instead of a decrease in Aβ42 levels, an increase in Aβ42 was observed in these individuals, leading to the proposal to refer to them as nondemented subjects with increased pTau-levels and Aβ surge with subtle cognitive deterioration (PASSED). In this study, we determined the longitudinal atrophy rates of AD, PASSED, and Biomarker-negative nondemented individuals of two independent cohorts to determine whether these groups can be distinguished by their longitudinal atrophy patterns or rates.

Methods

Depending on their CSF-levels of pTau 181 (T), total Tau (tTau, N), Aβ42 or ratio of Aβ42/Aβ40 (A), 185 non-demented subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and 62 non-demented subjects from Erlangen AD cohort were assigned to an ATN group (A-T-N-, A-T+N±, A+T-N±and A+T+N±) and underwent T1-weighted structural magnetic resonance imaging (sMRI). Longitudinal grey matter (GM) atrophy patterns were assessed with voxel-based morphometry (VBM) using the cat12 toolbox on spm12 (statistical parametric mapping) of MRI scans from individuals in the ADNI cohort with a mean follow-up of 2 and 5 years, respectively. The annualized atrophy rate for individuals in the Erlangen cohort was determined using region of interest analysis (ROI) in terms of a confirmatory analysis.

Results

In the A-T+N± group, VBM did not identify any brain region that showed greater longitudinal atrophy than the A+T+N±, A+T+N± or biomarker negative control group. In contrast, marked longitudinal atrophy in the temporal lobe was evident in the A+T-N± group compared with A+T-N±  and biomarker-negative subjects. The ROI in the angular gyrus identified by VBM analysis of the ADNI cohort did not discriminate better than the hippocampal volume and atrophy rate between AD and PASSED in the confirmatory analysis.

Discussion

In this study, nondemented subjects with PASSED did not show a unique longitudinal atrophy pattern in comparison to nondemented subjects with AD. The nonsignificant atrophy rate compared with controls suggests that increased pTau181-levels without concomitant amyloidopathy did not indicate a neurodegenerative disorder.

The Role of the Thioredoxin System in Brain Diseases

The thioredoxin system, consisting of thioredoxin (Trx), thioredoxin reductase (TrxR), and NADPH, plays a fundamental role in the control of antioxidant defenses, cell proliferation, redox states, and apoptosis. Aberrations in the Trx system may lead to increased oxidative stress toxicity and neurodegenerative processes. This study reviews the role of the Trx system in the pathophysiology and treatment of Alzheimer's, Parkinson's and Huntington's diseases, brain stroke, and multiple sclerosis. Trx system plays an important role in the pathophysiology of those disorders via multiple interactions through oxidative stress, apoptotic, neuro-immune, and pro-survival pathways. Multiple aberrations in Trx and TrxR systems related to other redox systems and their multiple reciprocal relationships with the neurodegenerative, neuro-inflammatory, and neuro-oxidative pathways are here analyzed. Genetic and environmental factors (nutrition, metals, and toxins) may impact the function of the Trx system, thereby contributing to neuropsychiatric disease. Aberrations in the Trx and TrxR systems could be a promising drug target to prevent and treat neurodegenerative, neuro-inflammatory, neuro-oxidative stress processes, and related brain disorders.

Medial Temporal Atrophy in Posterior Cortical Atrophy and Its Relationship to the Cingulate Island Sign

Background: It has been hypothesized that medial temporal sparing may be related to preserved posterior cingulate metabolism and the cingulate island sign (CIS) on [18F]fluorodeoxyglucose (FDG) PET in posterior cortical atrophy (PCA). Objective: To assess the severity of medial temporal atrophy in PCA and determine whether the presence of a CIS is related to medial temporal sparing. Methods: Fifty-five PCA patients underwent MRI and FDG-PET. The degree and symmetry of medial temporal atrophy on MRI was visually assessed using a five-point scale for both hemispheres. Visual assessments of FDG-PET coded the presence/absence of a CIS and whether the CIS was symmetric or asymmetric. Hippocampal volumes and a quantitative CIS were also measured. Results: Medial temporal atrophy was most commonly mild or moderate, was symmetric in 55% of patients, and when asymmetric was most commonly worse on the right (76%). Older age and worse memory performance were associated with greater medial temporal atrophy. The CIS was observed in 44% of the PCA patients and was asymmetric in 50% of these. The patients with a CIS showed greater medial temporal asymmetry, but did not show lower medial temporal atrophy scores, compared to those without a CIS. Hippocampal volumes were not associated with quantitative CIS. Conclusion: Mild medial temporal atrophy is a common finding in PCA and is associated with memory impairment. However, medial temporal sparing was not related to the presence of a CIS in PCA.

Entorhinal Subfield Vulnerability to Neurofibrillary Tangles in Aging and the Preclinical Stage of Alzheimer's Disease

BACKGROUND

Neurofibrillary tangle (NFT) accumulation in the entorhinal cortex (EC) precedes the transformation from cognitive controls to mild cognitive impairment and Alzheimer's disease (AD). While tauopathy has been described in the EC before, the order and degree to which the individual subfields within the EC are engulfed by NFTs in aging and the preclinical AD stage is unknown.

OBJECTIVE

We aimed to investigate substructures within the EC to map the populations of cortical neurons most vulnerable to tau pathology in aging and the preclinical AD stage.

METHODS

We characterized phosphorylated tau (CP13) in 10 cases at eight well-defined anterior-posterior levels and assessed NFT density within the eight entorhinal subfields (described by Insausti and colleagues) at the preclinical stages of AD. We validated with immunohistochemistry and labeled the NFT density ratings on ex vivo MRIs. We measured subfield cortical thickness and reconstructed the labels as three-dimensional isosurfaces, resulting in anatomically comprehensive, histopathologically validated tau "heat maps."

RESULTS

We found the lateral EC subfields ELc, ECL, and ECs (lateral portion) to have the highest tau density in semi-quantitative scores and quantitative measurements. We observed significant stepwise higher tau from anterior to posterior levels (p < 0.001). We report an age-dependent anatomically-specific vulnerability, with all cases showing posterior tau pathology, yet older individuals displaying an additional anterior tau burden. Finally, cortical thickness of each subfield negatively correlated with respective tau scores (p < 0.05).

CONCLUSION

Our findings indicate that posterior-lateral subfields within the EC are the most vulnerable to early NFTs and atrophy in aging and preclinical AD.

OUP accepted manuscript

Alzheimer’s disease-related atrophy in the posterior cingulate cortex, a key node of the default mode network, is present in the early stages of disease progression across clinical phenotypic variants of the disease. In the typical amnestic variant, posterior cingulate cortex neuropathology has been linked with disrupted connectivity of the posterior default mode network, but it remains unclear if this relationship is observed across atypical variants of Alzheimer’s disease. In the present study, we first sought to determine if tau pathology is consistently present in the posterior cingulate cortex and other posterior nodes of the default mode network across the atypical Alzheimer’s disease syndromic spectrum. Second, we examined functional connectivity disruptions within the default mode network and sought to determine if tau pathology is related to functional disconnection within this network. We studied a sample of 25 amyloid-positive atypical Alzheimer’s disease participants examined with high-resolution MRI, tau (¹⁸F-AV-1451) PET, and resting-state functional MRI. In these patients, high levels of tau pathology in the posteromedial cortex and hypoconnectivity between temporal and parietal nodes of the default mode network were observed relative to healthy older controls. Furthermore, higher tau signal and reduced grey matter density in the posterior cingulate cortex and angular gyrus were associated with reduced parietal functional connectivity across individual patients, related to poorer cognitive scores. Our findings converge with what has been reported in amnestic Alzheimer’s disease, and together these observations offer a unifying mechanistic feature that relates posterior cingulate cortex tau deposition to aberrant default mode network connectivity across heterogeneous clinical phenotypes of Alzheimer’s disease.

Connectomic mapping of brain-spinal cord neural networks: future directions in assessing spinal cord injury at rest

Following spinal cord injury (SCI), the central nervous system undergoes significant reconstruction. The dynamic change in the interaction of the brain-spinal cord axis as well as in structure-function relations plays a vital role in the determination of neurological functions, which might have important clinical implications for the treatment and its efficacy evaluation of patients with SCI. Brain connectomes based on neuroimaging data is a relatively new field of research that maps the brain's large-scale structural and functional networks at rest. Importantly, increasing evidence shows that such resting-state signals can also be seen in the spinal cord. In the present review, we focus on the reconstruction of multi-level neural circuits after SCI. We also describe how the connectome concept could further our understanding of neuroplasticity after SCI. We propose that mapping the cortical-subcortical-spinal cord networks can provide novel insights into the pathologies of SCI.

Baseline MRI atrophy predicts 2-year cognitive outcomes in early-onset Alzheimer's disease

BACKGROUND

MRI atrophy predicts cognitive status in AD. However, this relationship has not been investigated in early-onset AD (EOAD, < 65 years) patients with a biomarker-based diagnosis.

METHODS

Forty eight EOAD (MMSE ≥ 15; A + T + N +) and forty two age-matched healthy controls (HC; A - T - N -) from a prospective cohort underwent full neuropsychological assessment, 3T-MRI scan and lumbar puncture at baseline. Participants repeated the cognitive assessment annually. We used linear mixed models to investigate whether baseline cortical thickness (CTh) or subcortical volume predicts two-year cognitive outcomes in the EOAD group.

RESULTS

In EOAD, hemispheric CTh and ventricular volume at baseline were associated with global cognition, language and attentional/executive functioning 2 years later (p < 0.0028). Regional CTh was related to most cognitive outcomes (p < 0.0028), except verbal/visual memory subtests. Amygdalar volume was associated with letter fluency test (p < 0.0028). Hippocampal volume did not show significant associations.

CONCLUSION

Baseline hemispheric/regional CTh, ventricular and amygdalar volume, but not the hippocampus, predict two-year cognitive outcomes in EOAD.

Posterior Cingulate Cortex Hypometabolism in Non-Amnestic Variants of Alzheimer's Disease

BACKGROUND

Hypometabolism of the posterior cingulate cortex (PCC) is an important diagnostic feature of late-onset, amnestic Alzheimer's disease (AD) measured with 18F-fluorodeoxyglucose positron emission tomography (FDG-PET). However, it is unclear whether PCC hypometabolism has diagnostic value in young-onset, non-amnestic variants of AD, which exhibit less pathology in the hippocampus and default mode network.

OBJECTIVE

Evaluate the prevalence and diagnostic value of PCC hypometabolism in non-amnestic variants of AD.

METHODS

We retrospectively identified 60 patients with young-onset, atypical dementia who have undergone a detailed clinical evaluation, FDG-PET, and an amyloid biomarker (amyloid-PET or cerebrospinal fluid analysis). We quantitatively analyzed regional hypometabolism in 70 regions of interest (ROI) using the MIMneuro® software.

RESULTS

Based on a cut-off of z-score < -1.5 for significant PCC hypometabolism, the prevalence of PCC hypometabolism in non-amnestic variants of AD was 65% compared to 28% in clinical variants of frontotemporal dementia (FTD). The ROI with the maximal hypometabolism was the dominant middle temporal gyrus in the language variant of AD (mean z score -2.28), middle occipital gyrus in PCA (-3.24), middle temporal gyrus in frontal AD (-2.70), and angular gyrus in corticobasal syndrome due to AD (-2.31). The PCC was not among the 10 most discriminant regions between non-amnestic variants of AD versus clinical variants of FTD.

CONCLUSION

We conclude that PCC hypometabolism is not a discriminant feature to distinguish non-amnestic variants of AD from clinical variants of FTD-and should be interpreted with caution in patients with young-onset, non-amnestic dementia.

Posterior cortical atrophy phenotypic heterogeneity revealed by decoding 18F-FDG-PET

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. 18F-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.

Recent Advances in Imaging of Preclinical, Sporadic, and Autosomal Dominant Alzheimer's Disease

Observing Alzheimer's disease (AD) pathological changes in vivo with neuroimaging provides invaluable opportunities to understand and predict the course of disease. Neuroimaging AD biomarkers also allow for real-time tracking of disease-modifying treatment in clinical trials. With recent neuroimaging advances, along with the burgeoning availability of longitudinal neuroimaging data and big-data harmonization approaches, a more comprehensive evaluation of the disease has shed light on the topographical staging and temporal sequencing of the disease. Multimodal imaging approaches have also promoted the development of data-driven models of AD-associated pathological propagation of tau proteinopathies. Studies of autosomal dominant, early sporadic, and late sporadic courses of the disease have shed unique insights into the AD pathological cascade, particularly with regard to genetic vulnerabilities and the identification of potential drug targets. Further, neuroimaging markers of b-amyloid, tau, and neurodegeneration have provided a powerful tool for validation of novel fluid cerebrospinal and plasma markers. This review highlights some of the latest advances in the field of human neuroimaging in AD across these topics, particularly with respect to positron emission tomography and structural and functional magnetic resonance imaging.

Comparison of Alzheimer's disease patients and healthy controls in the easy Z-score imaging system with differential image reconstruction methods using SPECT/CT: verification using normal database of our institution

OBJECTIVE

The easy Z-score imaging system (eZIS) analysis is used for the diagnosis of dementia by cerebral blood flow on single photon emission computed tomography (SPECT). Differences in the acquisition and reconstruction conditions in SPECT may affect the eZIS analysis results. The present study aimed to construct our institutional normal database (NDB) and Alzheimer's disease (AD)-specific volumes of interest (VOIs) in eZIS analysis, and to compare the differential diagnostic ability between healthy controls (HC) and patients with AD in the image reconstruction filtered back projection (FBP) and ordered subset expectation maximization (OSEM) methods.

METHODS

An NDB was constructed at our institution from 30 healthy individual using the FBP and OSEM reconstruction methods. We divided 51 HC and 51 AD patients into two groups, one for AD disease-specific VOI construction (HC, AD) and the other for NDB verification (HC, AD); image reconstruction was performed using FBP and OSEM. The areas of reduced blood flow in AD patients were compared with those of HC using the two types of image reconstruction methods. We used AD disease-specific VOI and NDB from each reconstruction method in eZIS analysis and compared the differential diagnostic ability for HC and AD with the different reconstruction methods.

RESULTS

Comparing the areas of reduced blood flow in AD patients using the different image reconstruction methods, OSEM showed decreased blood flow in the medial region of the temporal lobes compared to FBP. Comparing the differential diagnostic ability for HC and AD using eZIS, the Severity, Extent, and Ratio showed higher values in the analysis performed using OSEM image reconstruction compared to FBP.

CONCLUSION

With the ^99mTc-ECD SPECT, the eZIS analysis equipped with our institutional AD-specific VOI and NDB using OSEM image reconstruction could distinguish HC from AD better than eZIS analysis using FBP image reconstruction. This study is registered in UMIN Clinical Trials Registry (UMIN-CTR) as UMIN study ID: UMIN000042362.

Posterior Cingulate Cortex Network Predicts Alzheimer's Disease Progression

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by the accumulation of toxic misfolded proteins, which are believed to have propagated from disease-specific epicenters through their corresponding large-scale structural networks in the brain. Although previous cross-sectional studies have identified potential AD-associated epicenters and corresponding brain networks, it is unclear whether these networks are associated with disease progression. Hence, this study aims to identify the most vulnerable epicenters and corresponding large-scale structural networks involved in the early stages of AD and to evaluate its associations with multiple cognitive domains using longitudinal study design. Annual neuropsychological and MRI assessments were obtained from 23 patients with AD, 37 patients with amnestic mild cognitive impairment (MCI), and 33 healthy controls (HC) for 3 years. Candidate epicenters were identified as regions with faster decline rate in the gray matter volume (GMV) in patients with MCI who progressed to AD as compared to those regions in patients without progression. These epicenters were then further used as pre-defined regions of interest to map the synchronized degeneration network (SDN) in HCs. Spatial similarity, network preference and clinical association analyses were used to evaluate the specific roles of the identified SDNs. Our results demonstrated that the hippocampus and posterior cingulate cortex (PCC) were the most vulnerable AD-associated epicenters. The corresponding PCC-SDN showed significant spatial association with the patterns of GMV atrophy rate in each patient group and the overlap of these patterns was more evident in the advanced stages of the disease. Furthermore, individuals with a higher GMV atrophy rate of the PCC-SDN also showed faster decline in multiple cognitive domains. In conclusion, our findings suggest the PCC and hippocampus are two vulnerable regions involved early in AD pathophysiology. However, the PCC-SDN, but not hippocampus-SDN, was more closely associated with AD progression. These results may provide insight into the pathophysiology of AD from large-scale network perspective.

Differential Involvement of the Locus Coeruleus in Early- and Late-Onset Alzheimer's Disease: A Potential Mechanism of Clinical Differences?

Early-onset Alzheimer's disease (EOAD) has been associated with an increased likelihood of atypical clinical manifestations such as attentional impairment, yet the cause of this heterogeneity remains unclear. The locus coeruleus (LC) is implicated early in Alzheimer's disease pathology and is associated with attentional functioning. This study investigated post-mortem atrophy of the LC in EOAD and late-onset Alzheimer's disease (LOAD) in a large, well-characterized sample. Results show nearly four times greater likelihood of higher LC atrophy in EOAD as compared to LOAD after controlling for other measures of pathological progression ( p < .005). Follow-up analyses within the EOAD group revealed that compared to those who displayed mild or no LC atrophy at autopsy, those with moderate-severe atrophy of the LC displayed significantly worse performance on various baseline measures of attentional functioning ( p < .05), despite similar overall cognition ( p = .25). These findings suggest the LC is an important potential driver of clinical and pathological heterogeneity in EOAD.

Neuropathologic burden and the degree of frailty in relation to global cognition and dementia

OBJECTIVE

To test the hypothesis that degree of frailty and neuropathologic burden independently contribute to global cognition and odds of dementia.

METHODS

This was a secondary analysis of a prospective cohort study of older adults living in Illinois. Participants underwent an annual neuropsychological and clinical evaluation. We included 625 participants (mean age 89.7 ± 6.1 years; 67.5% female) who died and underwent autopsy. We quantified neuropathology using an index measure of 10 neuropathologic features: β-amyloid deposition, hippocampal sclerosis, Lewy bodies, tangle density, TDP-43, cerebral amyloid angiopathy, arteriolosclerosis, atherosclerosis, and gross and chronic cerebral infarcts. Clinical consensus determined dementia status, which we coded as no cognitive impairment, mild cognitive impairment, or dementia. A battery of 19 tests spanning multiple domains quantified global cognition. We operationalized frailty using a 41-item frailty index. We employed regression analyses to model relationships between neuropathology, frailty, and dementia.

RESULTS

Both frailty and a neuropathology index were independently associated with global cognition and dementia status. These results held after controlling for traditional pathologic measures in a sample of participants with Alzheimer clinical syndrome. Frailty improved the fit of the model for dementia status (χ²[2] 72.64; p < 0.0001) and explained an additional 11%-12% of the variance in the outcomes.

CONCLUSION

Dementia is a multiply determined condition, to which both general health, as captured by frailty, and neuropathology significantly contribute. This integrative view of dementia and health has implications for prevention and therapy; specifically, future research should evaluate frailty as a means of dementia risk reduction.

Utility of Easy Z-Score Imaging System-Assisted SPECT in Detecting Onset Age-Dependent Decreases in Cerebral Blood Flow in the Posterior Cingulate Cortex, Precuneus, and Parietal Lobe in Alzheimer's Disease with Amyloid Accumulation

Background

Easy Z-score imaging system (eZIS)-assisted SPECT accurately detects decreases in cerebral blood flow in the posterior cingulate cortex (PCC), precuneus, and parietal lobe, the cerebral regions deeply implicated in Alzheimer's disease (AD). Several studies suggested onset age-dependent decreases in cerebral blood flow in these regions in AD, but these studies did not screen for amyloid accumulation, suggesting inclusion of non-AD patients in their subjects.

Objective

By applying eZIS-SPECT to patients with amyloid deposition, it was the aim of this study to clarify onset age-dependent decreases in cerebral blood flow in the regions critical to AD.

Methods

We retrospectively analyzed eZIS-SPECT data on 34 AD patients with amyloid retention confirmed by ¹¹C-Pittsburgh compound B-PET. The subjects were divided into an early-onset group (n = 16) and a late-onset group (n = 18). The three indicators of the eZIS that had discriminated between AD patients and normal controls in previous studies were compared between the two groups.

Results

The mean values for the respective indicators were significantly higher in the early-onset group than in the late-onset group. Also, the proportion of patients with abnormalities in all indicators was significantly higher in the early-onset group (93.8%) than in the late-onset group (50.0%).

Conclusions

The present study, applying eZIS-SPECT to amyloid-positive AD patients, suggests that reduced cerebral blood flow in the PCC, precuneus, and parietal lobe is more pronounced in the early-onset type than in the late-onset type of the disease.

Progressive dysexecutive syndrome due to Alzheimer's disease: a description of 55 cases and comparison to other phenotypes

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 18F-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 ε4 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.

M1 muscarinic acetylcholine receptor dysfunction in moderate Alzheimer's disease pathology

Aggregation of amyloid beta and loss of cholinergic innervation in the brain are predominant components of Alzheimer’s disease pathology and likely underlie cognitive impairment. Acetylcholinesterase inhibitors are one of the few treatment options for Alzheimer’s disease, where levels of available acetylcholine are enhanced to counteract the cholinergic loss. However, these inhibitors show limited clinical efficacy. One potential explanation for this is a concomitant dysregulation of cholinergic receptors themselves as a consequence of the amyloid beta pathology. We tested this hypothesis by examining levels of M1 muscarinic acetylcholine receptors in the temporal cortex from seven Alzheimer’s disease and seven non-disease age-matched control brain tissue samples (control: 85 ± 2.63 years old, moderate Alzheimer’s disease: 84 ± 2.32 years old, P-value = 0.721; eight female and six male patients). The samples were categorized into two groups: ‘control’ (Consortium to Establish a Registry for Alzheimer’s Disease diagnosis of ‘No Alzheimer’s disease’, and Braak staging pathology of I–II) and ‘moderate Alzheimer’s disease’ (Consortium to Establish a Registry for Alzheimer’s Disease diagnosis of ‘possible/probable Alzheimer’s disease’, and Braak staging pathology of IV). We find that in comparison to age-matched controls, there is a loss of M1 muscarinic acetylcholine receptors in moderate Alzheimer’s disease tissue (control: 2.17 ± 0.27 arbitrary units, n = 7, Mod-AD: 0.83 ± 0.16 arbitrary units, n = 7, two-tailed t-test, t = 4.248, P = 0.00113). Using a functional rat cortical brain slice model, we find that postsynaptic muscarinic acetylcholine receptor function is dysregulated by aberrant amyloid beta-mediated activation of metabotropic glutamate receptor 5. Crucially, blocking metabotropic glutamate receptor 5 restores muscarinic acetylcholine receptor function and object recognition memory in 5XFAD transgenic mice. This indicates that the amyloid beta-mediated activation of metabotropic glutamate receptor 5 negatively regulates muscarinic acetylcholine receptor and illustrates the importance of muscarinic acetylcholine receptors as a potential disease-modifying target in the moderate pathological stages of Alzheimer’s disease.

Network localization of clinical, cognitive, and neuropsychiatric symptoms in Alzheimer's disease

There is both clinical and neuroanatomical variability at the single-subject level in Alzheimer's disease, complicating our understanding of brain-behaviour relationships and making it challenging to develop neuroimaging biomarkers to track disease severity, progression, and response to treatment. Prior work has shown that both group-level atrophy in clinical dementia syndromes and complex neurological symptoms in patients with focal brain lesions localize to brain networks. Here, we use a new technique termed 'atrophy network mapping' to test the hypothesis that single-subject atrophy maps in patients with a clinical diagnosis of Alzheimer's disease will also localize to syndrome-specific and symptom-specific brain networks. First, we defined single-subject atrophy maps by comparing cortical thickness in each Alzheimer's disease patient versus a group of age-matched, cognitively normal subjects across two independent datasets (total Alzheimer's disease patients = 330). No more than 42% of Alzheimer's disease patients had atrophy at any given location across these datasets. Next, we determined the network of brain regions functionally connected to each Alzheimer's disease patient's location of atrophy using seed-based functional connectivity in a large (n = 1000) normative connectome. Despite the heterogeneity of atrophied regions at the single-subject level, we found that 100% of patients with a clinical diagnosis of Alzheimer's disease had atrophy functionally connected to the same brain regions in the mesial temporal lobe, precuneus cortex, and angular gyrus. Results were specific versus control subjects and replicated across two independent datasets. Finally, we used atrophy network mapping to define symptom-specific networks for impaired memory and delusions, finding that our results matched symptom networks derived from patients with focal brain lesions. Our study supports atrophy network mapping as a method to localize clinical, cognitive, and neuropsychiatric symptoms to brain networks, providing insight into brain-behaviour relationships in patients with dementia.

Functional Connectivity in Neurodegenerative Disorders: Alzheimer's Disease and Frontotemporal Dementia

Neurodegenerative disorders are a growing cause of morbidity and mortality worldwide. Onset is typically insidious and clinical symptoms of behavioral change, memory loss, or cognitive dysfunction may not be evident early in the disease process. Efforts have been made to discover biomarkers that allow for earlier diagnosis of neurodegenerative disorders, to initiate treatment that may slow the course of clinical deterioration. Neuronal dysfunction occurs earlier than clinical symptoms manifest. Thus, assessment of neuronal function using functional brain imaging has been examined as a potential biomarker. While most early studies used task-functional magnetic resonance imaging (fMRI), with the more recent technique of resting-state fMRI, "intrinsic" relationships between brain regions or brain networks have been studied in greater detail in neurodegenerative disorders. In Alzheimer's disease, the most common neurodegenerative disorder, and frontotemporal dementia, another of the common dementias, specific brain networks may be particularly susceptible to dysfunction. In this review, we highlight the major findings of functional connectivity assessed by resting state fMRI in Alzheimer's disease and frontotemporal dementia.

Early-onset Alzheimer Disease and Its Variants

PURPOSE OF REVIEW

Early-onset Alzheimer disease (AD) is defined as having an age of onset younger than 65 years. While early-onset AD is often overshadowed by the more common late-onset AD, recognition of the differences between early- and late-onset AD is important for clinicians.

RECENT FINDINGS

Early-onset AD comprises about 5% to 6% of cases of AD and includes a substantial percentage of phenotypic variants that differ from the usual amnestic presentation of typical AD. Characteristics of early-onset AD in comparison to late-onset AD include a larger genetic predisposition (familial mutations and summed polygenic risk), more aggressive course, more frequent delay in diagnosis, higher prevalence of traumatic brain injury, less memory impairment and greater involvement of other cognitive domains on presentation, and greater psychosocial difficulties. Neuroimaging features of early-onset AD in comparison to late-onset AD include greater frequency of hippocampal sparing and posterior neocortical atrophy, increased tau burden, and greater connectomic changes affecting frontoparietal networks rather than the default mode network.

SUMMARY

Early-onset AD differs substantially from late-onset AD, with different phenotypic presentations, greater genetic predisposition, and differences in neuropathologic burden and topography. Early-onset AD more often presents with nonamnestic phenotypic variants that spare the hippocampi and with greater tau burden in posterior neocortices. The early-onset AD phenotypic variants involve different neural networks than typical AD. The management of early-onset AD is similar to that of late-onset AD but with special emphasis on targeting specific cognitive areas and more age-appropriate psychosocial support and education.

How Big Data and High-performance Computing Drive Brain Science

Brain science accelerates the study of intelligence and behavior, contributes fundamental insights into human cognition, and offers prospective treatments for brain disease. Faced with the challenges posed by imaging technologies and deep learning computational models, big data and high-performance computing (HPC) play essential roles in studying brain function, brain diseases, and large-scale brain models or connectomes. We review the driving forces behind big data and HPC methods applied to brain science, including deep learning, powerful data analysis capabilities, and computational performance solutions, each of which can be used to improve diagnostic accuracy and research output. This work reinforces predictions that big data and HPC will continue to improve brain science by making ultrahigh-performance analysis possible, by improving data standardization and sharing, and by providing new neuromorphic insights.

Human cortical folding across regions within individual brains follows universal scaling law

Different cortical regions vary systematically in their morphology. Here we investigate if the scaling law of cortical morphology, which was previously demonstrated across both human subjects and mammalian species, still holds within a single cortex across different brain regions. By topologically correcting for regional curvature, we could analyse how different morphological parameters co-vary within single cortices. We show in over 1500 healthy individuals that, despite their morphological diversity, regions of the same cortex obey the same universal scaling law, and age morphologically at similar rates. In Alzheimer's disease, we observe a premature ageing in the morphological parameters that was nevertheless consistent with the scaling law. The premature ageing effect was most dramatic in the temporal lobe. Thus, while morphology can vary substantially across cortical regions, subjects, and species, it always does so in accordance with a common scaling law, suggesting that the underlying processes driving cortical gyrification are universal.

The role of age on tau PET uptake and gray matter atrophy in atypical Alzheimer's disease

INTRODUCTION

Little is known about the role of age on neurodegeneration and protein deposition in atypical variants of Alzheimer's disease (AD).

METHODS

Regional tau and β-amyloid positron emission tomography standard uptake value ratios and gray matter volumes were calculated in a cohort of 42 participants with atypical AD. The relationship between regional metrics and age was modeled using a Bayesian hierarchical linear model.

RESULTS

Age was strongly associated with tau uptake across all cortical regions, particularly parietal, with greater uptake in younger participants. Younger age was associated with smaller parietal and lateral temporal volumes. Regional β-amyloid differed little by age. Age showed a stronger association with tau than volume and β-amyloid in all cortical regions. Age was not associated with cognitive performance.

DISCUSSION

Age is an important determinant of severity of cortical tau uptake in atypical AD, with young participants more likely to show widespread and severe cortical tau uptake.

Temporal and regional progression of Alzheimer's disease-like pathology in 3xTg-AD mice

Accumulation of amyloid-β (Aβ) and fibrillary tangles, as well as neuroinflammation and memory loss, are hallmarks of Alzheimer's disease (AD). After almost 15 years from their generation, 3xTg-AD mice are still one of the most used transgenic models of AD. Converging evidence indicates that the phenotype of 3xTg-AD mice has shifted over the years and contradicting reports about onset of pathology or cognitive deficits are apparent in the literature. Here, we assessed Aβ and tau load, neuroinflammation, and cognitive changes in 2-, 6-, 12-, and 20-month-old female 3xTg-AD and nontransgenic (NonTg) mice. We found that ~80% of the mice analyzed had Aβ plaques in the caudal hippocampus at 6 months of age, while 100% of them had Aβ plaques in the hippocampus at 12 months of age. Cortical Aβ plaques were first detected at 12 months of age, including in the entorhinal cortex. Phosphorylated Tau at Ser202/Thr205 and Ser422 was apparent in the hippocampus of 100% of 6-month-old mice, while only 50% of mice showed tau phosphorylation at Thr212/Ser214 at this age. Neuroinflammation was first evident in 6-month-old mice and increased as a function of age. These neuropathological changes were clearly associated with progressive cognitive decline, which was first apparent at 6 months of age and became significantly worse as the mice aged. These data indicate a consistent and predictable progression of the AD-like pathology in female 3xTg-AD mice, and will facilitate the design of future studies using these mice.

Cingulate-centered large-scale networks: Normal functions, aging, and neurodegenerative disease

In this chapter, we review evidence from structural and functional neuroimaging in humans to consider the role of the cingulate cortex subregions (i.e., subgenual anterior cingulate cortex, pregenual anterior cingulate cortex, anterior midcingulate cortex, and dorsal posterior cingulate cortex) as major hubs anchoring multiple large-scale brain networks. We begin with a review of evidence from intrinsic functional connectivity and diffusion tensor imaging studies to show how connections within and between cingulate-centered networks contribute to processing and integrating signals related to autonomic, affective, executive, and memory functions. We then consider how variability in cingulate-centered networks could contribute to a range of aging outcomes, including typical aging and unusually successful aging (dubbed "superaging"), as well as early neurodegenerative dementias, including frontotemporal dementia and Alzheimer's disease.

The Action of Polyphenols in Diabetes Mellitus and Alzheimer's Disease: A Common Agent for Overlapping Pathologies

Diabetes Mellitus (DM) and Alzheimer's disease (AD) are two prevalent diseases in modern societies, which are caused mainly by current lifestyle, aging and genetic alterations. It has already been demonstrated that these two diseases are associated, since individuals suffering from DM are prone to develop AD. Conversely, it is also known that individuals with AD are more susceptible to DM, namely type 2 diabetes (T2DM). Therefore, these two pathologies, although completely different in terms of symptomatology, end up sharing several mechanisms at the molecular level, with the most obvious being the increase of oxidative stress and inflammation. Polyphenols are natural compounds widely spread in fruits and vegetables whose dietary intake has been considered inversely proportional to the incidence of DM and AD. So, it is believed that this group of phytochemicals may have preventive and therapeutic potential, not only by reducing the risk and delaying the development of these pathologies, but also by improving brain's metabolic profile and cognitive function. The aim of this review is to understand the extent to which DM and AD are related pathologies, the degree of similarity and the relationship between them, to detail the molecular mechanisms by which polyphenols may exert a protective effect, such as antioxidant and anti-inflammatory effects, and highlight possible advantages of their use as common preventive and therapeutic alternatives.

Prosodic and phonetic subtypes of primary progressive apraxia of speech

Primary progressive apraxia of speech (PPAOS) is a clinical syndrome in which apraxia of speech is the initial indication of neurodegenerative disease. Prior studies of PPAOS have identified hypometabolism, grey matter atrophy, and white matter tract degeneration in the frontal gyri, precentral cortex, and supplementary motor area (SMA). Recent clinical observations suggest two distinct subtypes of PPAOS may exist. Phonetic PPAOS is characterized predominantly by distorted sound substitutions. Prosodic PPAOS is characterized predominantly by slow, segmented speech. Demographic, clinical, and neuroimaging data (MRI, DTI, and FDG-PET) were analyzed to validate these subtypes and explore anatomic correlates. The Phonetic subtype demonstrated bilateral involvement of the SMA, precentral gyrus, and cerebellar crus. The Prosodic subtype demonstrated more focal involvement in the SMA and right superior cerebellar peduncle. The findings provide converging evidence that differences in the reliably determined predominant clinical characteristics of AOS are associated with distinct imaging patterns, independent of severity.

Development of a risk score for the prediction of incident dementia in older adults using a frailty index and health checkup data: The JAGES longitudinal study

In Japan, the prevalence of dementia is expected to reach 4.7 million by 2025. This study aimed to develop a risk score for the prediction of incident dementia in community-dwelling older adults. In this longitudinal observational study, we used data from the Japan Gerontological Evaluation Study (JAGES) conducted in K City. We performed Cox regression analyses to develop three risk score models for the prediction of incident dementia in older adults using a frailty index and health checkup data. Analyses of the area under the receiver operating characteristic curve were conducted to compare the models' predictive abilities. We identified 6656 (9.2%) individuals who developed incident dementia during the observation period. The C-statistics of the risk scores ranged from 0.733 to 0.790. The risk score models were able to predict incident dementia in older adults and may help non-medical professionals detect dementia risk at an early stage.

Imaging correlations of tau, amyloid, metabolism, and atrophy in typical and atypical Alzheimer's disease

INTRODUCTION

Neuroimaging modalities can measure different aspects of the disease process in Alzheimer's disease, although the relationship between these modalities is unclear.

METHODS

We assessed subject-level regional correlations between tau on [¹⁸F]AV-1451 positron emission tomography (PET), β amyloid on Pittsburgh compound B PET, hypometabolism on [¹⁸F] fluorodeoxyglucose PET, and cortical thickness on magnetic resonance imaging in 96 participants with typical and atypical Alzheimer's disease presentations. We also assessed how correlations between modalities varied according to age, presenting syndrome, tau-PET severity, and asymmetry.

RESULTS

[¹⁸F]AV-1451 uptake showed the strongest regional correlation with hypometabolism. Correlations between [¹⁸F]AV-1451 uptake and both hypometabolism and cortical thickness were stronger in participants with greater cortical tau severity. In addition, age, tau asymmetry, and clinical diagnosis influenced the strength of the correlation between [¹⁸F]AV-1451 uptake and cortical thickness.

DISCUSSION

These findings support a close relationship between tau and hypometabolism in Alzheimer's disease but show that correlations between neuroimaging modalities vary across participants.

The personalized Alzheimer's disease cortical thickness index predicts likely pathology and clinical progression in mild cognitive impairment

Introduction

An Alzheimer's disease (AD) biomarker adjusted for age-related brain changes should improve specificity for AD-related pathological burden.

Methods

We calculated a brain-age-adjusted “personalized AD cortical thickness index” (pADi) in mild cognitive impairment patients from the Alzheimer's Disease Neuroimaging Initiative. We performed receiver operating characteristic analysis for discrimination between patients with and without cerebrospinal fluid evidence of AD and logistic regression in an independent sample to determine if a dichotomized pADi predicted conversion to AD dementia.

Results

Receiver operating characteristic area under the curve was 0.69 and 0.72 in the two samples. Three empirical methods identified the same cut-point for pADi in the discovery sample. In the validation sample, 83% of pADi+ mild cognitive impairment patients were cerebrospinal fluid AD biomarker positive. pADi+ mild cognitive impairment patients (n = 63, 38%) were more likely to progress to AD dementia after 1 (odds ratio = 2.9) and 3 (odds ratio = 2.6) years.

Discussion

The pADi is a personalized, magnetic resonance imaging–derived AD biomarker that predicts progression to dementia.

•

The personalized AD cortical thickness index (pADi) is a personalized magnetic resonance imaging–derived, brain-age-adjusted Alzheimer's disease (AD) biomarker.

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The pADi accurately identifies mild cognitive impairment patients with cerebrospinal fluid markers of AD.

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The pADi was consistent across two independent samples with 1.5T and 3T magnetic resonance imaging data.

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An optimal cut-point predicted progression to AD dementia over 1 or 3 years.

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The pADi can identify mild cognitive impairment likely due to AD in individual patients.

[18 F]AV-1451 clustering of entorhinal and cortical uptake in Alzheimer's disease

OBJECTIVE

To use a cluster analysis of [18 F]AV-1451 tau-PET data to determine how subjects with Alzheimer's disease (AD) vary in the relative involvement of the entorhinal cortex and neocortex, and determine whether relative involvement of these two regions can help explain variability in age and clinical phenotype in AD.

METHODS

We calculated [18 F]AV-1451 uptake in entorhinal cortex and neocortex in 62 amyloid-positive AD patients (39 typical and 23 atypical presentation). tau-PET (positron emission tomography) values were normalized to the cerebellum to create standard uptake value ratios (SUVRs). tau-PET SUVRs were log-transformed and clustered blinded to clinical information into three groups using K-median cluster analysis. Demographics, clinical phenotype, cognitive performance, and apolipoprotein e4 frequency were compared across clusters.

RESULTS

The cluster analysis identified a cluster with low entorhinal and cortical uptake (ELo /CLo ), one with low entorhinal but high cortical uptake (ELo /CHi ), and one with high cortical and entorhinal uptake (EHi /CHi ). Clinical phenotype differed across clusters, with typical AD most commonly observed in the ELo /CLo and EHi /CHi clusters, and atypical AD most commonly observed in the ELo /CHi cluster. The ELo /CLo cluster had an older age at PET and onset than the other clusters. Apolipoprotein e4 frequency was lower in the ELo /CHi cluster. The EHi /CHi cluster had the worst memory impairment, whereas the ELo /CHi cluster had the worst impairment in nonmemory domains.

INTERPRETATION

This study demonstrates considerable variability in [18 F]AV-1451 tau-PET uptake in AD, but shows that a straightforward clustering based on entorhinal and cortical uptake maps well onto age and clinical presentation in AD. Ann Neurol 2018 Ann Neurol 2018;83:248-257.