Linking APOE-ε4, blood-brain barrier dysfunction, and inflammation to Alzheimer's pathology

The APOE-ε4 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-ε4 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-1β, IL-6, and IL-12p70; inflammation markers), and CSF p-Tau₁₈₁ and amyloid-β_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-ε4 genotype. This suggests that APOE-ε4-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.

Associations between pattern separation and hippocampal subfield structure and function vary along the lifespan: A 7 T imaging study

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.

State-of-the-art imaging of neuromodulatory subcortical systems in aging and Alzheimer's disease: Challenges and opportunities

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.

Ultra-high field imaging, plasma markers and autopsy data uncover a specific rostral locus coeruleus vulnerability to hyperphosphorylated tau

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.

Shades of white: diffusion properties of T1- and FLAIR-defined white matter signal abnormalities differ in stages from cognitively normal to dementia

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.

Elevated Norepinephrine Metabolism Gauges Alzheimer's Disease-Related Pathology and Memory Decline

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.

Inter-network connectivity and amyloid-beta linked to cognitive decline in preclinical Alzheimer's disease: a longitudinal cohort study

BACKGROUND

Amyloid-beta (Aβ) has a dose-response relationship with cognition in healthy adults. Additionally, the levels of functional connectivity within and between brain networks have been associated with cognitive performance in healthy adults. Aiming to explore potential synergistic effects, we investigated the relationship of inter-network functional connectivity, Aβ burden, and memory decline among healthy individuals and individuals with preclinical, prodromal, or clinical Alzheimer's disease.

METHODS

In this longitudinal cohort study (ADNI2), participants (55-88 years) were followed for a maximum of 5 years. We included cognitively healthy participants and patients with mild cognitive impairment (with or without elevated Aβ) or Alzheimer's disease. Associations between memory decline, Aβ burden, and connectivity between networks across the groups were investigated using linear and curvilinear mixed-effects models.

RESULTS

We found a synergistic relationships between inter-network functional connectivity and Aβ burden on memory decline. Dose-response relationships between Aβ and memory decline varied as a function of directionality of inter-network connectivity across groups. When inter-network correlations were negative, the curvilinear mixed-effects models revealed that higher Aβ burden was associated with greater memory decline in cognitively normal participants, but when inter-network correlations were positive, there was no association between the magnitude of Aβ burden and memory decline. Opposite patterns were observed in patients with mild cognitive impairment. Combining negative inter-network correlations with Aβ burden can reduce the required sample size by 88% for clinical trials aiming to slow down memory decline.

CONCLUSIONS

The direction of inter-network connectivity provides additional information about Aβ burden on the rate of expected memory decline, especially in the preclinical phase. These results may be valuable for optimizing patient selection and decreasing study times to assess efficacy in clinical trials.

Prediction of clinical and biomarker conformed Alzheimer's disease and mild cognitive impairment from multi-feature brain structural MRI using age-correction from a large independent lifespan sample

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 AD 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.

Identifying individuals with Alzheimer's disease-like brains based on structural imaging in the Human Connectome Project Aging cohort

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.

Alzheimer's Disease Biomarkers Have Distinct Associations with Specific Hippocampal Subfield Volumes

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.

Heterogeneity of Cerebral White Matter Lesions and Clinical Correlates in Older Adults

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.

Multiscale structural mapping of Alzheimer's disease neurodegeneration

The recently described biological framework of Alzheimer's disease (AD) emphasizes three types of pathology to characterize this disorder, referred to as the 'amyloid/tau/neurodegeneration' (A-T-N) status. The 'neurodegenerative' component is typically defined by atrophy measures derived from structural magnetic resonance imaging (MRI) such as hippocampal volume. Neurodegeneration measures from imaging are associated with disease symptoms and prognosis. Thus, sensitive image-based quantification of neurodegeneration in AD has an important role in a range of clinical and research operations. Although hippocampal volume is a sensitive metric of neurodegeneration, this measure is impacted by several clinical conditions other than AD and therefore lacks specificity. In contrast, selective regional cortical atrophy, known as the 'cortical signature of AD' provides greater specificity to AD pathology. Although atrophy is apparent even in the preclinical stages of the disease, it is possible that increased sensitivity to degeneration could be achieved by including tissue microstructural properties in the neurodegeneration measure. However, to facilitate clinical feasibility, such information should be obtainable from a single, short, noninvasive imaging protocol. We propose a multiscale MRI procedure that advances prior work through the quantification of features at both macrostructural (morphometry) and microstructural (tissue properties obtained from multiple layers of cortex and subcortical white matter) scales from a single structural brain image (referred to as 'multi-scale structural mapping'; MSSM). Vertex-wise partial least squares (PLS) regression was used to compress these multi-scale structural features. When contrasting patients with AD to cognitively intact matched older adults, the MSSM procedure showed substantially broader regional group differences including areas that were not statistically significant when using cortical thickness alone. Further, with multiple machine learning algorithms and ensemble procedures, we found that MSSM provides accurate detection of individuals with AD dementia (AUROC = 0.962, AUPRC = 0.976) and individuals with mild cognitive impairment (MCI) that subsequently progressed to AD dementia (AUROC = 0.908, AUPRC = 0.910). The findings demonstrate the critical advancement of neurodegeneration quantification provided through multiscale mapping. Future work will determine the sensitivity of this technique for accurately detecting individuals with earlier impairment and biomarker positivity in the absence of impairment.

The canonical pattern of Alzheimer's disease atrophy is linked to white matter hyperintensities in normal controls, differently in normal controls compared to in AD

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.

Distinct Patterns Link the BDNF Val66Met Polymorphism to Alzheimer's Disease Pathology

The brain-derived neurotropic growth factor (BDNF) gene has been linked to dementia, inflammation, and Apolipoprotein E (APOE) ɛ4 status. We used cerebrospinal fluid (CSF) amyloid-β (Aβ)42 and phosphorylated tau (p-tau) to investigate associations with BDNF polymorphisms and modifications by APOE ɛ4 or inflammation in a memory clinic population (n = 114; subjective cognitive decline, mild cognitive impairment, Alzheimer's disease). We found distinct pathways to Alzheimer's disease pathology: Val-Met displayed lower CSF-Aβ 42 in APOE ɛ4+ carriers, independent of p-tau, while Val-Val displayed greater p-tau at higher IL-6 and sub-threshold Aβ 42. This may contribute to resolving some inconsistencies in the BDNF literature and provide possible inroads to specific Aβ and tau interventions depending on BDNF polymorphism.

Lower in vivo locus coeruleus integrity is associated with lower cortical thickness in older individuals with elevated Alzheimer's pathology: a cohort study

BACKGROUND

Autopsy work indicates that the widely-projecting noradrenergic pontine locus coeruleus (LC) is among the earliest regions to accumulate hyperphosphorylated tau, a neuropathological Alzheimer's disease (AD) hallmark. This early tau deposition is accompanied by a reduced density of LC projections and a reduction of norepinephrine's neuroprotective effects, potentially compromising the neuronal integrity of LC's cortical targets. Previous studies suggest that lower magnetic resonance imaging (MRI)-derived LC integrity may signal cortical tissue degeneration in cognitively healthy, older individuals. However, whether these observations are driven by underlying AD pathology remains unknown. To that end, we examined potential effect modifications by cortical beta-amyloid and tau pathology on the association between in vivo LC integrity, as quantified by LC MRI signal intensity, and cortical neurodegeneration, as indexed by cortical thickness.

METHODS

A total of 165 older individuals (74.24 ± 9.72 years, ~ 60% female, 10% cognitively impaired) underwent whole-brain and dedicated LC 3T-MRI, Pittsburgh Compound-B (PiB, beta-amyloid) and Flortaucipir (FTP, tau) positron emission tomography. Linear regression analyses with bootstrapped standard errors (n = 2000) assessed associations between bilateral cortical thickness and i) LC MRI signal intensity and, ii) LC MRI signal intensity interacted with cortical FTP or PiB (i.e., EC FTP, IT FTP, neocortical PiB) in the entire sample and a low beta-amyloid subsample.

RESULTS

Across the entire sample, we found a direct effect, where lower LC MRI signal intensity was associated with lower mediolateral temporal cortical thickness. Evaluation of potential effect modifications by FTP or PiB revealed that lower LC MRI signal intensity was related to lower cortical thickness, particularly in individuals with elevated (EC, IT) FTP or (neocortical) PiB. The latter result was present starting from subthreshold PiB values. In low PiB individuals, lower LC MRI signal intensity was related to lower EC cortical thickness in the context of elevated EC FTP.

CONCLUSIONS

Our findings suggest that LC-related cortical neurodegeneration patterns in older individuals correspond to regions representing early Braak stages and may reflect a combination of LC projection density loss and emergence of cortical AD pathology. This provides a novel understanding that LC-related cortical neurodegeneration may signal downstream consequences of AD-related pathology, rather than being exclusively a result of aging.

Lower Locus Coeruleus Integrity Signals Elevated Entorhinal Tau and Clinical Progression in Asymptomatic Older Individuals

OBJECTIVE

Elevated entorhinal cortex (EC) tau in low beta-amyloid individuals can predict accumulation of pathology and cognitive decline. We compared the accuracy of magnetic resonance imaging (MRI)-derived locus coeruleus integrity, neocortical beta-amyloid burden by positron emission tomography (PET), and hippocampal volume in identifying elevated entorhinal tau signal in asymptomatic individuals who are considered beta-amyloid PET-negative.

METHODS

We included 188 asymptomatic individuals (70.78 ± 11.51 years, 58% female) who underwent 3T-MRI of the locus coeruleus, Pittsburgh compound-B (PiB), and Flortaucipir (FTP) PET. Associations between elevated EC tau and neocortical PiB, hippocampal volume, or locus coeruleus integrity were evaluated and compared using logistic regression and receiver operating characteristic analyses in the PiB- sample with a clinical dementia rating (CDR) of 0. Associations with clinical progression (CDR-sum-of-boxes) over a time span of 6 years were evaluated with Cox proportional hazard models.

RESULTS

We identified 26 (21%) individuals with high EC FTP in the CDR = 0/PiB- sample. Locus coeruleus integrity was a significantly more sensitive and specific predictor of elevated EC FTP (area under the curve [AUC] = 85%) compared with PiB (AUC = 77%) or hippocampal volume (AUC = 76%). Based on the Youden-index, locus coeruleus integrity obtained a sensitivity of 77% and 85% specificity. Using the resulting locus coeruleus Youden cut-off, lower locus coeruleus integrity was associated with a two-fold increase in clinical progression, including mild cognitive impairment.

INTERPRETATION

Locus coeruleus integrity has promise as a low-cost, non-invasive screening instrument to detect early cortical tau deposition and associated clinical progression in asymptomatic, low beta-amyloid individuals. ANN NEUROL 2024;96:650-661.

Sparse Asymmetry in Locus Coeruleus Pathology in Alzheimer's Disease

 Tau accumulation in and neurodegeneration of locus coeruleus (LC) neurons is observed in Alzheimer's disease (AD). We investigated whether tangle and neuronal density in the rostral and caudal LC is characterized by an asymmetric pattern in 77 autopsy cases of the Rush Memory and Aging Project. We found left-right equivalence for tangle density across individuals with and without AD pathology. However, neuronal density, particularly in the caudal-rostral axis of the LC, is asymmetric among individuals with AD pathology. Asymmetry in LC neuronal density may signal advanced disease progression and should be considered in AD neuroimaging studies of LC neurodegeneration.