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White matter signal abnormalities (WMSA), either hypo- or hyperintensities in MRI imaging, are considered a proxy of cerebrovascular pathology and contribute to, and modulate, the clinical presentation of Alzheimer's disease (AD), with cognitive dysfunction being apparent at lower levels of amyloid and/or tau pathology when lesions are present. To what extent the topography of cortical thinning associated with AD may be explained by WMSA remains unclear. Cortical thickness group difference maps and subgroup analyses show that the effect of WMSA on cortical thickness in cognitively normal participants has a higher overlap with the canonical pattern of AD, compared to AD participants. (Age and sex-matched group of 119 NC (AV45 PET negative, CDR = 0) versus 119 participants with AD (AV45 PET-positive, CDR > 0.5). The canonical patterns of cortical atrophy thought to be specific to Alzheimer's disease are strongly linked to cerebrovascular pathology supporting a reinterpretation of the classical models of AD suggesting that a part of the typical AD pattern is due to co-localized cortical loss before the onset of AD.

Autopsy data indicate that the locus coeruleus (LC) is one of the first sites in the brain to accumulate hyperphosphorylated tau pathology, with the rostral part possibly being more vulnerable in the earlier stages of the disease. Taking advantage of recent developments in ultra-high field (7 T) imaging, we investigated whether imaging measures of the LC also reveal a specific anatomic correlation with tau using novel plasma biomarkers of different species of hyperphosphorylated tau, how early in adulthood these associations can be detected and if are associated with worse cognitive performance. To validate the anatomic correlations, we tested if a rostro-caudal gradient in tau pathology is also detected at autopsy in data from the Rush Memory and Aging Project (MAP). We found that higher plasma measures of phosphorylated tau, in particular ptau231, correlated negatively with dorso-rostral LC integrity, whereas correlations for neurodegenerative plasma markers (neurofilament light, total tau) were scattered throughout the LC including middle to caudal sections. In contrast, the plasma Aβ42/40 ratio, associated with brain amyloidosis, did not correlate with LC integrity. These findings were specific to the rostral LC and not observed when using the entire LC or the hippocampus. Furthermore, in the MAP data, we observed higher rostral than caudal tangle density in the LC, independent of the disease stage. The in vivo LC-phosphorylated tau correlations became significant from midlife, with the earliest effect for ptau231, starting at about age 55. Finally, interactions between lower rostral LC integrity and higher ptau231 concentrations predicted lower cognitive performance. Together, these findings demonstrate a specific rostral vulnerability to early phosphorylated tau species that can be detected with dedicated magnetic resonance imaging measures, highlighting the promise of LC imaging as an early marker of AD-related processes.

Primary prevention trials have shifted their focus to the earliest stages of Alzheimer's disease (AD). Autopsy data indicates that the neuromodulatory subcortical systems' (NSS) nuclei are specifically vulnerable to initial tau pathology, indicating that these nuclei hold great promise for early detection of AD in the context of the aging brain. The increasing availability of new imaging methods, ultra-high field scanners, new radioligands, and routine deep brain stimulation implants has led to a growing number of NSS neuroimaging studies on aging and neurodegeneration. Here, we review findings of current state-of-the-art imaging studies assessing the structure, function, and molecular changes of these nuclei during aging and AD. Furthermore, we identify the challenges associated with these imaging methods, important pathophysiologic gaps to fill for the AD NSS neuroimaging field, and provide future directions to improve our assessment, understanding, and clinical use of in vivo imaging of the NSS.

The locus coeruleus (LC) supplies norepinephrine to the brain, is one of the first sites of tau deposition in Alzheimer's disease (AD) and modulates a variety of behaviors and cognitive functions. Transgenic mouse models showed that norepinephrine dysregulation after LC lesions exacerbates inflammatory responses, blood-brain barrier leakage (BBB), and cognitive deficits. Here, we investigated relationships between central norepinephrine metabolism, tau and beta-amyloid (Aβ), inflammation, BBB-dysfunction, neuropsychiatric problems, and memory in-vivo in a memory clinic population (total n = 111, 60 subjective cognitive decline, 36 mild cognitively impaired, and 19 AD dementia). Cerebrospinal fluid (CSF) and blood samples were collected and analyzed for 3-methoxy-4-hydroxyphenylethyleneglycol (MHPG), CSF/plasma albumin ratio (Q-alb), Aβ, phosphorylated tau, and interleukins. The verbal word learning task and the neuropsychiatric inventory assessed memory functioning and neuropsychiatric symptoms. Structural equation models tested the relationships between all fluid markers, cognition and behavior, corrected for age, education, sex, and clinical dementia rating score. Our results showed that neuropsychiatric symptoms show strong links to both MHPG and p-tau, whereas memory deficits are linked to MHPG via a combination of p-tau and inflammation-driven amyloidosis (30-35% indirect effect contribution). These results suggest that the LC-norepinephrine may be pivotal to understand links between AD pathology and behavioral and cognitive deficits in AD.

The noradrenergic (NE) locus coeruleus (LC) is vulnerable to hyperphosphorylated tau, and dysregulated NE-metabolism is linked to greater tau and disease progression. We investigated whether elevated NE-metabolism alone predicts memory decline or whether concomitant presence of tau and amyloid-β is required. Among 114 memory clinic participants, time trends (max. six years) showed dose-response declines in learning across groups with elevated NE-metabolite 3-methoxy-4-hydroxyphenylethyleneglycol (MHPG) with no, one, or two Alzheimer’s disease biomarkers; and no decline in the low MHPG group. Elevated MHPG is required and sufficient to detect learning declines, supporting a pathophysiologic model including the LC-NE system contributing to initial Alzheimer’s disease-related processes.

Given the difficulty in factoring out typical age effects from subtle Alzheimer's disease (AD) effects on brain structure, identification of very early, as well as younger preclinical “at‐risk” individuals has unique challenges. We examined whether age‐correction procedures could be used to better identify individuals at very early potential risk from adults who did not have any existing cognitive diagnosis. First, we obtained cross‐sectional age effects for each structural feature using data from a selected portion of the Human Connectome Project Aging (HCP‐A) cohort. After age detrending, we weighted AD structural deterioration with patterns quantified from data of the Alzheimer's Disease Neuroimaging Initiative. Support vector machine was then used to classify individuals with brains that most resembled atrophy in AD across the entire HCP‐A sample. Additionally, we iteratively adjusted the pipeline by removing individuals classified as AD‐like from the HCP‐A cohort to minimize atypical brain structural contributions to the age detrending. The classifier had a mean cross‐validation accuracy of 94.0% for AD recognition. It also could identify mild cognitive impairment with more severe AD‐specific biomarkers and worse cognition. In an independent HCP‐A cohort, 8.8% were identified as AD‐like, and they trended toward worse cognition. An “AD risk” score derived from the machine learning models also significantly correlated with cognition. This work provides a proof of concept for the potential to use structural brain imaging to identify asymptomatic individuals at young ages who show structural brain patterns similar to AD and are potentially at risk for a future clinical disorder., The study provides a proof of concept for the potential to use structural brain imaging to identify asymptomatic individuals at young ages who show structural brain patterns similar to AD and are potentially at risk for a future clinical disorder. Our classifier could identify mild cognitive impairment with more severe AD‐specific biomarkers and worse cognition, as well as AD‐like individuals who trended toward worse cognition from a community‐based cohort.

Background and Purpose: Cerebral white matter signal abnormalities (WMSAs) are a significant radiological marker associated with brain and vascular aging. However, understanding their clinical impact is limited because of their pathobiological heterogeneity. We determined whether use of robust reliable automated procedures can distinguish WMSA classes with different clinical consequences. Methods: Data from generally healthy participants aged >50 years with moderate or greater WMSA were selected from the Human Connectome Project-Aging (n=130). WMSAs were segmented on T1 imaging. Features extracted from WMSA included total and regional volume, number of discontinuous clusters, size of noncontiguous lesion, contrast of lesion intensity relative to surrounding normal appearing tissue using a fully automated procedure. Hierarchical clustering was used to classify individuals into distinct classes of WMSA. Radiological and clinical variability was evaluated across the individual WMSA classes. Results: Class I was characterized by multiple, small, lower-contrast lesions predominantly in the deep WM; class II by large, confluent lesions in the periventricular WM; and class III by higher-contrast lesions restricted to the juxtaventricular WM. Class II was associated with lower myelin content than the other 2 classes. Class II was more prevalent in older subjects and was associated with a higher prevalence of hypertension and lower physical activity levels. Poor sleep quality was associated with a greater risk of class I. Conclusions: We classified heterogeneous subsets of cerebral white matter lesions into distinct classes that have different clinical risk factors. This new method for identifying classes of WMSA will be important in understanding the underlying pathophysiology and in determining the impact on clinical outcomes.

Pattern separation (PS) describes the process by which the brain discriminates similar stimuli from previously encoded stimuli. This fundamental process requires the intact processing by specific subfields in the hippocampus and can be examined using mnemonic discrimination tasks. Previous studies reported different patterns for younger and older individuals between mnemonic discrimination performance and hippocampal subfield activation. Here, we investigated the relationship between the lure discrimination index (LDI) and hippocampal subfield volume and activity across the adult lifespan (20–70 years old). Using ultra-high field functional and structural magnetic resonance imaging at 7 T, we found that lower DG volume and higher CA3 activation was associated with worse LDI performance in individuals (>60 years), suggesting that this higher activation may be an indication of aberrant neurodegenerative-related processes. In fact, higher activation in the CA1 and DG was associated with lower volumes in these subfields. For individuals around 40–50 years old, we observed that greater left and right DG volume, and greater activity in the CA3 was associated with lower LDI performance. Taken together, these results suggest that the relationship between memory and hippocampal subfield structure or function varies nonlinearly and possibly reciprocally with age, with midlife being a critically vulnerable period in life.

The APOE-epsilon 4 genotype is a risk factor for late-onset Alzheimer's disease (AD) as well as vascular pathology. Given the increased risk of blood-brain barrier (BBB) dysfunction and inflammation among APOE-epsilon 4 carriers, we aimed to examine whether BBB dysfunction and inflammation contribute to the relationship between APOE and AD key pathologies, as measured in the cerebrospinal fluid (CSF). We applied bootstrapped regression and path analyses involving Q-albumin CSF/plasma ratio (a BBB/blood-CSF barrier function marker), interleukins (IL-1 beta, IL-6, and IL-12p70; inflammation markers), and CSF p-Tau(181) and amyloid-beta(1-42) (AD pathology markers) of 97 participants (aged 38-83 years) from a university memory clinic. Our results showed that relationship between BBB dysfunction and AD pathology is modulated by IL-6 and these associations appear to be driven by the APOE-epsilon 4 genotype. This suggests that APOE-epsilon 4-related vascular factors are also part of the pathway to AD pathology, in synergy with an elevated immune response, and could become targets for trials focused on delaying AD. (C) 2019 The Author(s). Published by Elsevier Inc.

The underlying pathology of white matter signal abnormalities (WMSAs) is heterogeneous and may vary dependent on the magnetic resonance imaging contrast used to define them. We investigated differences in white matter diffusivity as an indicator for white matter integrity underlying WMSA based on T1-weighted and fluid-attenuated inversion recovery (FLAIR) imaging contrast. In addition, we investigated which white matter region of interest (ROI) could predict clinical diagnosis best using diffusion metrics. One hundred three older individuals with varying cognitive impairment levels were included and underwent neuroimaging. Diffusion metrics were extracted from WMSA areas based on T1 and FLAIR contrast and from their overlapping areas, the border surrounding the WMSA and the normal-appearing white matter (NAWM). Regional diffusivity differences were calculated with linear mixed effects models. Multinomial logistic regression determined which ROI diffusion values classified individuals best into clinically defined diagnostic groups. T1-based WMSA showed lower white matter integrity compared to FLAIR WMSA-defined regions. Diffusion values of NAWM predicted diagnostic group best compared to other ROI's. To conclude, T1- or FLAIR-defined WMSA provides distinct information on the underlying white matter integrity associated with cognitive decline. Importantly, not the "diseased" but the NAWM is a potentially sensitive indicator for cognitive brain health status.

The locus coeruleus (LC) supplies norepinephrine to the brain, is one of the first sites of tau deposition in Alzheimer's disease (AD) and modulates a variety of behaviors and cognitive functions. Transgenic mouse models showed that norepinephrine dysregulation after LC lesions exacerbates inflammatory responses, blood-brain barrier leakage (BBB), and cognitive deficits. Here, we investigated relationships between central norepinephrine metabolism, tau and beta-amyloid (Aβ), inflammation, BBB-dysfunction, neuropsychiatric problems, and memory in-vivo in a memory clinic population (total n = 111, 60 subjective cognitive decline, 36 mild cognitively impaired, and 19 AD dementia). Cerebrospinal fluid (CSF) and blood samples were collected and analyzed for 3-methoxy-4-hydroxyphenylethyleneglycol (MHPG), CSF/plasma albumin ratio (Q-alb), Aβ, phosphorylated tau, and interleukins. The verbal word learning task and the neuropsychiatric inventory assessed memory functioning and neuropsychiatric symptoms. Structural equation models tested the relationships between all fluid markers, cognition and behavior, corrected for age, education, sex, and clinical dementia rating score. Our results showed that neuropsychiatric symptoms show strong links to both MHPG and p-tau, whereas memory deficits are linked to MHPG via a combination of p-tau and inflammation-driven amyloidosis (30-35% indirect effect contribution). These results suggest that the LC-norepinephrine may be pivotal to understand links between AD pathology and behavioral and cognitive deficits in AD.

Highlights • Age correction based on lifespan sample and structural MRI help AD classification. • The classifier generalizes well in new dataset with different racial compositions. • The classifier could differentiate AD biomarkers in mild cognitive impairment. • The classifier recognized mild cognitive impairment with faster cognitive decline., Structural neuroimaging has been applied to the identification of individuals with Alzheimer’s disease (AD) and mild cognitive impairment (MCI). However, these methods are greatly impacted by age limiting their utility for detection of preclinical pathology. We built linear models for age based on multiple combined structural features using a large independent lifespan sample of 272 healthy adults across a wide age range from the Human Connectome Project Aging study. These models were then used to create a new support vector machine (SVM) training model in 136 CE and 268 control participants based on residues of fit from the expected age-effects relationship. Subsequent validation assessed the accuracy of the SVM model in new datasets. Finally, we applied the classifier to 276 individuals with MCI to evaluate prediction for early impairment and longitudinal cognitive change. The optimal 10-fold cross-validation accuracy was 93.07%, compared to 91.83% without age detrending. In the validation dataset, the classifier for AD obtained an accuracy of 84.85% (56/66), sensitivity of 85.36% (35/41) and specificity of 84% (21/25). Classification accuracy was improved when using the lifespan sample as opposed to the classification sample. Importantly, we observed cross-sectional greater AD specific biomarkers, as well as faster cognitive decline in MCI who were classified as more ‘AD-like’ (MCI-AD), and these effects were pronounced in individuals who were late MCI. The top five contributive features were volumes of left hippocampus, right hippocampus, left amygdala, the thickness of left and right middle temporal & parahippocampus gyrus. Linear detrending for age in SVM for combined structural features resulted in good performance for recognition of AD and AD-specific biomarkers, as well as prediction of MCI progression. Such procedures may be used in future work to enhance prediction in samples with atypical age distributions.

Measures of amyloid-β (Aβ) and phosphorylated tau (p-tau) concentrations in cerebrospinal fluid are extensively used for diagnostic and research purposes in Alzheimer's disease (AD) as correlates of cortical thinning and cognitive outcomes. The present study investigated the relationship of Aβ and p-tau with hippocampal subfield volumes Cornu Ammonis (CA) 1-4, dentate gyrus (DG), and subiculum. Subfields were segmented from T1-weighted images from the ADNI-population using FreeSurfer v6. Linear and polynomial regression models revealed distinct associations of Aβ and p-tau with subfield volumes. Aβ had a quadratic relationship with all hippocampal subfield volumes and the inflection point was higher than the validated cut-off for Aβ. For p-tau the relationships were linear, except for CA3, in which it was quadratic. For the CA1 and CA3, these quadratic relationships with Aβ were only observed when p-tau was low. Amyloid and p-tau contributed equally to the explained variance in CA4 and DG volume. Subicular volume was best explained by Aβ alone. These biomarker relationships with hippocampal subfield volumes seem to mirror the hippocampal-specific topography of Aβ and tau reported in neuropathological staging models. In addition, using continuous values of Aβ reveals positive patterns with imaging markers for individuals around the positivity threshold that would be masked when using dichotomized biomarker groups, which can be important for early detection and accurate inclusion of potential participants at risk for AD in clinical trials.

This article provides an overview of the methods used for optical surface imaging during the last 30 years, with the primary focus on the imaging of the unsedated child. The goal is to provide the reader with an overview of the working methods behind the published articles. This will enable the reader to better interpret current data and decide if a certain approach is suitable for their particular research question.

Direct vagus nerve stimulation (dVNS) is known to improve mood, epilepsy, and memory. Memory improvements have been observed in Alzheimer's disease patients after long-term stimulation. The potential of transcutaneous vagus nerve stimulation (tVNS), a noninvasive alternative to dVNS, to alter memory performance remains unknown. We aimed to investigate the effect of a single-session tVNS on associative memory performance in healthy older individuals. To investigate this, we performed a single-blind sham-controlled randomized crossover pilot study in healthy older individuals (n = 30, 50% female). During the stimulation or sham condition, participants performed an associative face-name memory task. tVNS enhanced the number of hits of the memory task, compared with the sham condition. This effect was specific to the experimental task. Participants reported few side effects. We conclude that tVNS is a promising neuromodulatory technique to improve associative memory performance in older individuals, even after a single session. More research is necessary to investigate its underlying neural mechanisms, the impact of varying stimulation parameters, and its applicability in patients with cognitive decline.