Gray matter hypoperfusion is a late pathological event in the course of Alzheimer's disease

Hypertension and cerebral blood flow in the development of Alzheimer's disease

INTRODUCTION

We investigated the interactive associations between amyloid and hypertension on the entorhinal cortex (EC) tau and atrophy and the role of cerebral blood flow (CBF) as a shared mechanism by which amyloid and hypertension contribute to EC tau and regional white matter hyperintensities (WMHs).

METHODS

We analyzed data from older adults without dementia participating in the Add-Tau study (NCT02958670, n = 138) or Alzheimer's Disease Neuroimaging Initiative (ADNI) (n = 523) who had available amyloid-positron emission tomography (PET), tau-PET, fluid-attenuated inversion recovery (FLAIR), and T1-weighted magnetic resonance imaging (MRI). A subsample in both cohorts had available arterial spin labeling (ASL) MRI (Add-Tau: n = 78; ADNI: n = 89).

RESULTS

The detrimental effects of hypertension on AD pathology and EC thickness were more pronounced in the Add-Tau cohort. Increased amyloid burden was associated with decreased occipital gray matter CBF in the ADNI cohort. In both cohorts, lower regional gray matter CBF was associated with higher EC tau and posterior WMH burden.

DISCUSSION

Reduced cerebral perfusion may be one common mechanism through which hypertension and amyloid are related to increased EC tau and WMH volume.

HIGHLIGHTS

Hypertension is associated with increased entorhinal cortex (EC) tau, particularly in the presence of amyloid. Decreased cortical cerebral blood flow (CBF) is associated with higher regional white matter hyperintensity volume. Increasing amyloid burden is associated with decreasing CBF in the occipital lobe. MTL CBF and amyloid are synergistically associated with EC tau.

Time-encoded ASL reveals lower cerebral blood flow in the early AD continuum

INTRODUCTION

Cerebral blood flow (CBF) is reduced in cognitively impaired (CI) Alzheimer's disease (AD) patients. We checked the sensitivity of time-encoded arterial spin labeling (te-ASL) in measuring CBF alterations in individuals with positive AD biomarkers and associations with relevant biomarkers in cognitively unimpaired (CU) individuals.

METHODS

We compared te-ASL with single-postlabel delay (PLD) ASL in measuring CBF in 59 adults across the AD continuum, classified as CU amyloid beta (Aβ) negative (-), CU Aβ positive (+), and CI Aβ+. We sought associations of CBF with biomarkers of AD, cerebrovascular disease, synaptic dysfunction, neurodegeneration, and cognition in CU participants.

RESULTS

te-ASL was more sensitive at detecting CBF reduction in the CU Aβ+ and CI Aβ+ groups. In CU participants, lower CBF was associated with altered biomarkers of Aβ, tau, synaptic dysfunction, and neurodegeneration.

DISCUSSION

CBF reduction occurs early in the AD continuum. te-ASL is more sensitive than single-PLD ASL at detecting CBF changes in AD.

HIGHLIGHTS

Lower CBF can be detected in CU subjects in the early AD continuum. te-ASL is more sensitive than single-PLD ASL at detecting CBF alterations in AD. CBF is linked to biomarkers of AD, synaptic dysfunction, and neurodegeneration.

Vascular contributions to cognitive decline: Beyond amyloid and tau in the Harvard Aging Brain Study

In addition to amyloid and tau pathology, elevated systemic vascular risk, white matter injury, and reduced cerebral blood flow contribute to late-life cognitive decline. Given the strong collinearity among these parameters, we proposed a framework to extract the independent latent features underlying cognitive decline using the Harvard Aging Brain Study (N = 166 cognitively unimpaired older adults at baseline). We used the following measures from the baseline visit: cortical amyloid, inferior temporal cortex tau, relative cerebral blood flow, white matter hyperintensities, peak width of skeletonized mean diffusivity, and Framingham Heart Study cardiovascular disease risk. We used exploratory factor analysis to extract orthogonal factors from these variables and their interactions. These factors were used in a regression model to explain longitudinal Preclinical Alzheimer Cognitive Composite-5 (PACC) decline (follow-up = 8.5 ±2.7 years). We next examined whether gray matter volume atrophy acts as a mediator of factors and PACC decline. Latent factors of systemic vascular risk, white matter injury, and relative cerebral blood flow independently explain cognitive decline beyond amyloid and tau. Gray matter volume atrophy mediates these associations with the strongest effect on white matter injury. These results suggest that systemic vascular risk contributes to cognitive decline beyond current markers of cerebrovascular injury, amyloid, and tau.

Data-driven modelling of neurodegenerative disease progression: thinking outside the black box

Data-driven disease progression models are an emerging set of computational tools that reconstruct disease timelines for long-term chronic diseases, providing unique insights into disease processes and their underlying mechanisms. Such methods combine a priori human knowledge and assumptions with large-scale data processing and parameter estimation to infer long-term disease trajectories from short-term data. In contrast to 'black box' machine learning tools, data-driven disease progression models typically require fewer data and are inherently interpretable, thereby aiding disease understanding in addition to enabling classification, prediction and stratification. In this Review, we place the current landscape of data-driven disease progression models in a general framework and discuss their enhanced utility for constructing a disease timeline compared with wider machine learning tools that construct static disease profiles. We review the insights they have enabled across multiple neurodegenerative diseases, notably Alzheimer disease, for applications such as determining temporal trajectories of disease biomarkers, testing hypotheses about disease mechanisms and uncovering disease subtypes. We outline key areas for technological development and translation to a broader range of neuroscience and non-neuroscience applications. Finally, we discuss potential pathways and barriers to integrating disease progression models into clinical practice and trial settings.

NOX-induced oxidative stress is a primary trigger of major neurodegenerative disorders

Neurodegenerative diseases (NDDs) causing cognitive impairment and dementia are difficult to treat due to the lack of understanding of primary initiating factors. Meanwhile, major sporadic NDDs share many risk factors and exhibit similar pathologies in their early stages, indicating the existence of common initiation pathways. Glucose hypometabolism associated with oxidative stress is one such primary, early and shared pathology, and a likely major cause of detrimental disease-associated cascades; targeting this common pathology may therefore be an effective preventative strategy for most sporadic NDDs. However, its exact cause and trigger remain unclear. Recent research suggests that early oxidative stress caused by NADPH oxidase (NOX) activation is a shared initiating mechanism among major sporadic NDDs and could prove to be the long-sought ubiquitous NDD trigger. We focus on two major NDDs - Alzheimer's disease (AD) and Parkinson's disease (PD), as well as on acquired epilepsy which is an increasingly recognized comorbidity in NDDs. We also discuss available data suggesting the relevance of the proposed mechanisms to other NDDs. We delve into the commonalities among these NDDs in neuroinflammation and NOX involvement to identify potential therapeutic targets and gain a deeper understanding of the underlying causes of NDDs.