Effect of vascular amyloid on white matter disease is mediated by vascular dysfunction in cerebral amyloid angiopathy

Neurovascular coupling in early stage dementia - A case-control study

Cerebral amyloid angiopathy (CAA) is frequently found post mortem in Alzheimer's dementia, but often undetected during life especially since in vivo hallmarks of CAA and its vascular damage become overt relatively late in the disease process. Decreased neurovascular coupling to visual stimulation has been put forward as an early MRI marker for CAA disease severity. The current study investigates the role of neurovascular coupling in AD related dementia and its early stages. We included 25 subjective cognitive impairment, 33 mild cognitive impairment and 17 dementia patients and 44 controls. All participants underwent magnetic resonance imaging of the brain and neuropsychological assessment. Univariate general linear modeling analyses were used to assess neurovascular coupling between patient groups and controls. Moreover, linear regression analyses was used to assess the associations between neurovascular coupling and cognition. Our data show that BOLD amplitude is lower in dementia (mean 0.8 ± 0.2, p = 0.001) and MCI patients (mean 0.9 ± 0.3, p = 0.004) compared with controls (mean 1.1 ± 0.2). A low BOLD amplitude was associated with low scores in multiple cognitive domains. We conclude that cerebrovascular dysfunction, most likely due CAA, is an important comorbidity in early stages of dementia and has an independent effect on cognition.

In-vivo diagnosis of cerebral amyloid angiopathy: an updated review

PURPOSE OF REVIEW

Sporadic cerebral amyloid angiopathy (CAA) is a highly prevalent small vessel disease in ageing population with potential severe complications including lobar intracerebral hemorrhage (ICH), cognitive impairment, and dementia. Although diagnosis of CAA was made only with postmortem neuropathological examination a few decades ago, diagnosing CAA without pathological proof is now allowed in living patients. This review focuses on recently identified biomarkers of CAA and current diagnostic criteria.

RECENT FINDINGS

Over the past few years, clinicians and researchers have shown increased interest for CAA, and important advances have been made. Thanks to recent insights into mechanisms involved in CAA and advances in structural and functional neuroimaging, PET amyloid tracers, cerebrospinal fluid and plasma biomarkers analysis, a growing number of biomarkers of CAA have been identified. Imaging-based diagnostic criteria including emerging biomarkers have been recently developed or updated, enabling accurate and earlier diagnosis of CAA in living patients.

SUMMARY

Recent advances in neuroimaging allow diagnosing CAA in the absence of pathological examination. Current imaging-based criteria have high diagnostic performance in patients presenting with ICH, but is more limited in other clinical context such as cognitively impaired patients or asymptomatic individuals. Further research is still needed to improve diagnostic accuracy.

Cerebral amyloid deposition predicts long-term cognitive decline in hemorrhagic small vessel disease

BACKGROUND

To investigate the association between cerebral amyloid deposition and long-term cognitive outcomes in patients with hemorrhagic small vessel disease (SVD) and survivors of intracerebral hemorrhage (ICH).

METHODS

Patients experiencing an ICH without overt dementia were prospectively recruited (n = 68) for brain MRI and Pittsburgh compound B (PiB) positron emission tomography scans at baseline. Cognitive function was assessed using the mini-mental status examination (MMSE) and clinical dementia rating after an overall median follow-up of 3.8 years. A positive amyloid scan was defined as a global PiB standardized uptake value ratio >1.2. Associations between follow-up cognitive outcomes and neuroimaging markers were explored using multivariable Cox regression models.

RESULTS

PiB(+) patients were older (72.1 ± 7.8 vs. 59.9 ± 11.7, p = .002) and more frequently had cerebral amyloid angiopathy (CAA) (63.6% vs. 15.8%, p = .002) than PiB(-) patients. PiB(+) was associated with a higher risk of dementia conversion (32.9 vs. 4.0 per 100-person-years, hazard ratio [HR] = 15.7 [3.0-80.7], p = .001) and MMSE score decline (58.8 vs. 9.9 per 100-person-years, HR = 6.2 [1.9-20.0], p = .002). In the non-CAA subgroup (n = 52), PiB(+) remained an independent predictor of dementia conversion, p = .04). In the Cox models, PiB(+) was an independent predictor of dementia conversion (HR = 15.8 [2.6-95.4], p = .003) and MMSE score decline (HR = 5.7 [1.6-20.3], p = .008) after adjusting for confounders.

CONCLUSIONS

Cerebral amyloid deposition potentially contributes to long-term cognitive decline in SVD-related ICH.

Progression of cerebral amyloid angiopathy: a pathophysiological framework

Cerebral amyloid angiopathy, which is defined by cerebrovascular deposition of amyloid β, is a common age-related small vessel pathology associated with intracerebral haemorrhage and cognitive impairment. Based on complementary lines of evidence from in vivo studies of individuals with hereditary, sporadic, and iatrogenic forms of cerebral amyloid angiopathy, histopathological analyses of affected brains, and experimental studies in transgenic mouse models, we present a framework and timeline for the progression of cerebral amyloid angiopathy from subclinical pathology to the clinical manifestation of the disease. Key stages that appear to evolve sequentially over two to three decades are (stage one) initial vascular amyloid deposition, (stage two) alteration of cerebrovascular physiology, (stage three) non-haemorrhagic brain injury, and (stage four) appearance of haemorrhagic brain lesions. This timeline of stages and the mechanistic processes that link them have substantial implications for identifying disease-modifying interventions for cerebral amyloid angiopathy and potentially for other cerebral small vessel diseases.

The cross-sectional association between amyloid burden and white matter hyperintensities in older adults without cognitive impairment: A systematic review and meta-analysis

Alzheimer's disease (AD) is the most common cause of dementia, characterized by the aggregation of amyloid-beta (Aβ) proteins into plaques. Individuals with AD frequently show mixed pathologies, often caused by cerebral small vessel disease (CSVD), resulting in lesions such as white matter hyperintensities (WMH). The current systematic review and meta-analysis investigated the cross-sectional relationship between amyloid burden and WMH in older adults without objective cognitive impairment. A systematic search performed in PubMed, Embase, and PsycINFO yielded 13 eligible studies. Aβ was assessed using PET, CSF, or plasma measurements. Two meta-analyses were performed: one on Cohen's d metrics and one on correlation coefficients. The meta-analyses revealed an overall weighted small-to-medium Cohen's d of 0.55 (95% CI: 0.31-0.78) in CSF, an overall correlation of 0.31 (0.09-0.50) in CSF, and a large Cohen's d of 0.96 (95% CI: 0.66-1.27) in PET. Only two studies assessed this relationship in plasma, with an effect size of - 0.20 (95% CI: -0.75 to 0.34). These findings indicate a relationship between both amyloid and vascular pathologies in cognitively normal adults in PET and CSF. Future studies should assess the possible relationship of blood amyloid-beta and WMH for broader identification of at risk individuals showing mixed pathology in preclinical stages.

Modeling the dynamics of cerebrovascular reactivity to carbon dioxide in fMRI under task and resting-state conditions

Conventionally, cerebrovascular reactivity (CVR) is estimated as the amplitude of the hemodynamic response to vascular stimuli, most commonly carbon dioxide (CO₂). While the CVR amplitude has established clinical utility, the temporal characteristics of CVR (dCVR) have been increasingly explored and may yield even more pathology-sensitive parameters. This work is motivated by the current need to evaluate the feasibility of dCVR modeling in various experimental conditions. In this work, we present a comparison of several recently published/utilized model-based deconvolution (response estimation) approaches for estimating the CO₂ response function h(t), including maximum a posteriori likelihood (MAP), inverse logit (IL), canonical correlation analysis (CCA), and basis expansion (using Gamma and Laguerre basis sets). To aid the comparison, we devised a novel simulation framework that incorporates a wide range of SNRs, ranging from 10 to -7 dB, representative of both task and resting-state CO₂ changes. In addition, we built ground-truth h(t) into our simulation framework, overcoming the conventional limitation that the true h(t) is unknown. Moreover, to best represent realistic noise found in fMRI scans, we extracted noise from in-vivo resting-state scans. Furthermore, we introduce a simple optimization of the CCA method (CCA_opt) and compare its performance to these existing methods. Our findings suggest that model-based methods can accurately estimate dCVR even amidst high noise (i.e. resting-state), and in a manner that is largely independent of the underlying model assumptions for each method. We also provide a quantitative basis for making methodological choices, based on the desired dCVR parameters, the estimation accuracy and computation time. The BEL method provided the highest accuracy and robustness, followed by the CCA_opt and IL methods. Of the three, the CCA_opt method has the lowest computational requirements. These findings lay the foundation for wider adoption of dCVR estimation in CVR mapping.

PET imaging for the evaluation of cerebral amyloid angiopathy: a systematic review

Purpose

In the last years, the role of PET imaging in the assessment of cerebral amyloid angiopathy (CAA) is emerging. In this setting, some tracers have proven their utility for the evaluation of the disease (mainly 11C-Pittsburgh compound B [11C-PIB]), however, the value of other radiotracers has to be clarified. The aim of this systematic review is, therefore, to assess the role of PET imaging in the evaluation of CAA.

Methods

A wide literature search of the PubMed/MEDLINE, Scopus, Embase, Web of Science and Cochrane library databases was made to find relevant published articles about the diagnostic performance of PET imaging for the evaluation of CAA. Quality assessment including the risk of bias and applicability concerns was carried out using QUADAS-2 evaluation.

Results

The comprehensive computer literature search revealed 651 articles. On reviewing the titles and abstracts, 622 articles were excluded because the reported data were not within the field of interest. Twenty-nine studies were included in the review. In general, PET imaging with amyloid tracers revealed its value for the assessment of CAA, for its differential diagnosis and a correlation with some clinico-pathological features. With less evidence, a role for 18F-fluorodeoxiglucose (18F-FDG) and tau tracers is starting to emerge.

Conclusion

PET imaging demonstrated its utility for the assessment of CAA. In particular, amiloid tracers revealed higher retention in CAA patients, correlation with cerebral bleed, the ability to differentiate between CAA and other related conditions (such as Alzheimer's disease) and a correlation with some cerebrospinal fluid biomarkers.