Biomarkers of cerebrovascular disease in dementia

Multi-Method Analysis of Medical Records and MRI Images for Early Diagnosis of Dementia and Alzheimer’s Disease Based on Deep Learning and Hybrid Methods

Dementia and Alzheimer’s disease are caused by neurodegeneration and poor communication between neurons in the brain. So far, no effective medications have been discovered for dementia and Alzheimer’s disease. Thus, early diagnosis is necessary to avoid the development of these diseases. In this study, efficient machine learning algorithms were assessed to evaluate the Open Access Series of Imaging Studies (OASIS) dataset for dementia diagnosis. Two CNN models (AlexNet and ResNet-50) and hybrid techniques between deep learning and machine learning (AlexNet+SVM and ResNet-50+SVM) were also evaluated for the diagnosis of Alzheimer’s disease. For the OASIS dataset, we balanced the dataset, replaced the missing values, and applied the t-Distributed Stochastic Neighbour Embedding algorithm (t-SNE) to represent the high-dimensional data in the low-dimensional space. All of the machine learning algorithms, namely, Support Vector Machine (SVM), Decision Tree, Random Forest and K Nearest Neighbours (KNN), achieved high performance for diagnosing dementia. The random forest algorithm achieved an overall accuracy of 94% and precision, recall and F1 scores of 93%, 98% and 96%, respectively. The second dataset, the MRI image dataset, was evaluated by AlexNet and ResNet-50 models and AlexNet+SVM and ResNet-50+SVM hybrid techniques. All models achieved high performance, but the performance of the hybrid methods between deep learning and machine learning was better than that of the deep learning models. The AlexNet+SVM hybrid model achieved accuracy, sensitivity, specificity and AUC scores of 94.8%, 93%, 97.75% and 99.70%, respectively.

Blood-Brain Barrier Breakdown: An Emerging Biomarker of Cognitive Impairment in Normal Aging and Dementia

The blood–brain barrier (BBB) plays a vital role in maintaining the specialized microenvironment of the neural tissue. It separates the peripheral circulatory system from the brain parenchyma while facilitating communication. Alterations in the distinct physiological properties of the BBB lead to BBB breakdown associated with normal aging and various neurodegenerative diseases. In this review, we first briefly discuss the aging process, then review the phenotypes and mechanisms of BBB breakdown associated with normal aging that further cause neurodegeneration and cognitive impairments. We also summarize dementia such as Alzheimer's disease (AD) and vascular dementia (VaD) and subsequently discuss the phenotypes and mechanisms of BBB disruption in dementia correlated with cognition decline. Overlaps between AD and VaD are also discussed. Techniques that could identify biomarkers associated with BBB breakdown are briefly summarized. Finally, we concluded that BBB breakdown could be used as an emerging biomarker to assist to diagnose cognitive impairment associated with normal aging and dementia.

Re-thinking the Etiological Framework of Neurodegeneration

Neurodegenerative diseases are among the leading causes of disability and death worldwide. The disease-related socioeconomic burden is expected to increase with the steadily increasing life expectancy. In spite of decades of clinical and basic research, most strategies designed to manage degenerative brain diseases are palliative. This is not surprising as neurodegeneration progresses "silently" for decades before symptoms are noticed. Importantly, conceptual models with heuristic value used to study neurodegeneration have been constructed retrospectively, based on signs and symptoms already present in affected patients; a circumstance that may confound causes and consequences. Hence, innovative, paradigm-shifting views of the etiology of these diseases are necessary to enable their timely prevention and treatment. Here, we outline four alternative views, not mutually exclusive, on different etiological paths toward neurodegeneration. First, we propose neurodegeneration as being a secondary outcome of a primary cardiovascular cause with vascular pathology disrupting the vital homeostatic interactions between the vasculature and the brain, resulting in cognitive impairment, dementia, and cerebrovascular events such as stroke. Second, we suggest that the persistence of senescent cells in neuronal circuits may favor, together with systemic metabolic diseases, neurodegeneration to occur. Third, we argue that neurodegeneration may start in response to altered body and brain trophic interactions established via the hardwire that connects peripheral targets with central neuronal structures or by means of extracellular vesicle (EV)-mediated communication. Lastly, we elaborate on how lifespan body dysbiosis may be linked to the origin of neurodegeneration. We highlight the existence of bacterial products that modulate the gut-brain axis causing neuroinflammation and neuronal dysfunction. As a concluding section, we end by recommending research avenues to investigate these etiological paths in the future. We think that this requires an integrated, interdisciplinary conceptual research approach based on the investigation of the multimodal aspects of physiology and pathophysiology. It involves utilizing proper conceptual models, experimental animal units, and identifying currently unused opportunities derived from human data. Overall, the proposed etiological paths and experimental recommendations will be important guidelines for future cross-discipline research to overcome the translational roadblock and to develop causative treatments for neurodegenerative diseases.

A Systematic Review and Implementation of IoT-Based Pervasive Sensor-Enabled Tracking System for Dementia Patients

In today's world, 46.8 million people suffer from brain related diseases. Dementia is most prevalent of all. In general scenario, a dementia patient lacks proper guidance in searching out the way to return back at his/her home. Thus, increasing the risk of getting damaged at individual-health level. Therefore, it is important to track their movement in more sophisticated manner as possible. With emergence of wearables, GPS sensors and Internet of Things (IoT), such devices have become available in public domain. Smartphone apps support caregiver to locate the dementia patients in real-time. RF, GSM, 3G, Wi-Fi and 4G technology fill the communication gap between patient and caregiver to bring them closer. In this paper, we incorporated 7 most popular wearables for investigation to seek appropriateness for dementia tracking in recent times in systematic manners. We performed an in-depth review of these wearables as per the cost, technology wise and application wise characteristics. A case novel study i.e. IoT-based Force Sensor Resistance enabled System-FSRIoT, has been proposed and implemented to validate the effectiveness of IoT in the domain of smarter dementia patient tracking in wearable form factor. The results show promising aspect of a whole new notion to leverage efficient assistive physio-medical healthcare to the dementia patients and the affected family members to reduce life risks and achieve a better social life.

Measurement of microvascular cerebral blood volume changes over the cardiac cycle with ferumoxytol-enhanced T2 * MRI

PURPOSE

This feasibility study investigates the non-invasive measurement of microvascular cerebral blood volume (BV) changes over the cardiac cycle using cardiac-gated, ferumoxytol-enhanced T 2 ∗ MRI.

METHODS

Institutional review board approval was obtained and all subjects provided written informed consent. Cardiac gated MR scans were prospectively acquired on a 3.0T scanner in 22 healthy subjects using T 2 ∗ -weighted sequences with 2D-EPI and 3D spiral trajectories. Images were collected before and after the intravenous administration of 2 doses of ferumoxytol (1 mg FE/kg and 4 mg FE/kg). Cardiac cycle-induced R 2 ∗ (1/ T 2 ∗ ) changes (Δ R 2 ∗ ) and BV changes (ΔBV) throughout the cardiac cycle in gray matter (GM) and white matter (WM) were quantified and differences assessed using ANOVA followed by post hoc analysis.

RESULTS

Δ R 2 ∗ was found to increase in a dose-dependent fashion. A significantly larger increase was observed in GM compared to WM in both 2D and 3D acquisitions (P < 0.050). In addition, Δ R 2 ∗ increased significantly (P < 0.001) post versus pre-contrast injection in GM in both T 2 ∗ MRI acquisitions. Mean GM Δ R 2 ∗ derived from 2D-EPI images was 0.14 ± 0.06 s^-1 pre-contrast and 0.33 ± 0.13 s^-1 after 5 mg FE/kg. In WM, Δ R 2 ∗ was 0.19 ± 0.06 s^-1 pre-contrast, and 0.23 ± 0.06 s^-1 after 5 mg FE/kg. The fractional changes in BV throughout the cardiac cycle were 0.031 ± 0.019% in GM and 0.011 ± 0.008% in WM (P < 0.001) after 5 mg FE/kg.

CONCLUSION

Cardiac-gated, ferumoxytol-enhanced T 2 ∗ MRI enables characterization of microvascular BV changes throughout the cardiac cycle in GM and WM tissue of healthy subjects.

Neuroimaging and Machine Learning for Dementia Diagnosis: Recent Advancements and Future Prospects

Dementia, a chronic and progressive cognitive declination of brain function caused by disease or impairment, is becoming more prevalent due to the aging population. A major challenge in dementia is achieving accurate and timely diagnosis. In recent years, neuroimaging with computer-aided algorithms have made remarkable advances in addressing this challenge. The success of these approaches is mostly attributed to the application of machine learning techniques for neuroimaging. In this review paper, we present a comprehensive survey of automated diagnostic approaches for dementia using medical image analysis and machine learning algorithms published in the recent years. Based on the rigorous review of the existing works, we have found that, while most of the studies focused on Alzheimer's disease, recent research has demonstrated reasonable performance in the identification of other types of dementia remains a major challenge. Multimodal imaging analysis deep learning approaches have shown promising results in the diagnosis of these other types of dementia. The main contributions of this review paper are as follows. 1) Based on the detailed analysis of the existing literature, this paper discusses neuroimaging procedures for dementia diagnosis. 2) It systematically explains the most recent machine learning techniques and, in particular, deep learning approaches for early detection of dementia.

Enlarged perivascular spaces in brain MRI: Automated quantification in four regions

Enlarged perivascular spaces (PVS) are structural brain changes visible in MRI, are common in aging, and are considered a reflection of cerebral small vessel disease. As such, assessing the burden of PVS has promise as a brain imaging marker. Visual and manual scoring of PVS is a tedious and observer-dependent task. Automated methods would advance research into the etiology of PVS, could aid to assess what a "normal" burden is in aging, and could evaluate the potential of PVS as a biomarker of cerebral small vessel disease. In this work, we propose and evaluate an automated method to quantify PVS in the midbrain, hippocampi, basal ganglia and centrum semiovale. We also compare associations between (earlier established) determinants of PVS and visual PVS scores versus the automated PVS scores, to verify whether automated PVS scores could replace visual scoring of PVS in epidemiological and clinical studies. Our approach is a deep learning algorithm based on convolutional neural network regression, and is contingent on successful brain structure segmentation. In our work we used FreeSurfer segmentations. We trained and validated our method on T2-contrast MR images acquired from 2115 subjects participating in a population-based study. These scans were visually scored by an expert rater, who counted the number of PVS in each brain region. Agreement between visual and automated scores was found to be excellent for all four regions, with intraclass correlation coefficients (ICCs) between 0.75 and 0.88. These values were higher than the inter-observer agreement of visual scoring (ICCs between 0.62 and 0.80). Scan-rescan reproducibility was high (ICCs between 0.82 and 0.93). The association between 20 determinants of PVS, including aging, and the automated scores were similar to those between the same 20 determinants of PVS and visual scores. We conclude that this method may replace visual scoring and facilitate large epidemiological and clinical studies of PVS.

Assessment of blood flow velocity and pulsatility in cerebral perforating arteries with 7-T quantitative flow MRI

Thus far, blood flow velocity measurements with MRI have only been feasible in large cerebral blood vessels. High-field-strength MRI may now permit velocity measurements in much smaller arteries. The aim of this proof of principle study was to measure the blood flow velocity and pulsatility of cerebral perforating arteries with 7-T MRI. A two-dimensional (2D), single-slice quantitative flow (Qflow) sequence was used to measure blood flow velocities during the cardiac cycle in perforating arteries in the basal ganglia (BG) and semioval centre (CSO), from which a mean normalised pulsatility index (PI) per region was calculated (n = 6 human subjects, aged 23-29 years). The precision of the measurements was determined by repeated imaging and performance of a Bland-Altman analysis, and confounding effects of partial volume and noise on the measurements were simulated. The median number of arteries included was 14 in CSO and 19 in BG. In CSO, the average velocity per volunteer was in the range 0.5-1.0 cm/s and PI was 0.24-0.39. In BG, the average velocity was in the range 3.9-5.1 cm/s and PI was 0.51-0.62. Between repeated scans, the precision of the average, maximum and minimum velocity per vessel decreased with the size of the arteries, and was relatively low in CSO and BG compared with the M1 segment of the middle cerebral artery. The precision of PI per region was comparable with that of M1. The simulations proved that velocities can be measured in vessels with a diameter of more than 80 µm, but are underestimated as a result of partial volume effects, whilst pulsatility is overestimated. Blood flow velocity and pulsatility in cerebral perforating arteries have been measured directly in vivo for the first time, with moderate to good precision. This may be an interesting metric for the study of haemodynamic changes in aging and cerebral small vessel disease. © 2015 The Authors NMR in Biomedicine Published by John Wiley & Sons Ltd.

Imaging the Perivascular Space as a Potential Biomarker of Neurovascular and Neurodegenerative Diseases

Although the brain lacks conventional lymphatic vessels found in peripheral tissue, evidence suggests that the space surrounding the vasculature serves a similar role in the clearance of fluid and metabolic waste from the brain. With aging, neurodegeneration, and cerebrovascular disease, these microscopic perivascular spaces can become enlarged, allowing for visualization and quantification on structural MRI. The purpose of this review is to: (i) describe some of the recent pre-clinical findings from basic science that shed light on the potential neurophysiological mechanisms driving glymphatic and perivascular waste clearance, (ii) review some of the pathobiological etiologies that may lead to MRI-visible enlarged perivascular spaces (ePVS), (iii) describe the possible clinical implications of ePVS, (iv) evaluate existing qualitative and quantitative techniques used for measuring ePVS burden, and (v) propose future avenues of research that may improve our understanding of this potential clinical neuroimaging biomarker for fluid and metabolic waste clearance dysfunction in neurodegenerative and neurovascular diseases.

(123)I-FP-CIT SPECT imaging in early diagnosis of dementia in patients with and without a vascular component

Alzheimer’s disease (AD) and vascular dementia (VaD) are the most common cause of dementia. Cerebral ischemia is a major risk factor for development of dementia. ¹²³I-FP-CIT SPECT (DaTScan) is a complementary tool in the differential diagnoses of patients with incomplete or uncertain Parkinsonism. Additional application of DaTScan enables the categorization of Parkinsonian disease with dementia (PDD), and its differentiation from pure AD, and may further contribute to change the therapeutic decision. The aim of this study was to analyze the vascular contribution towards dementia and mild cognitive impairment (MCI). We evaluated the utility of DaTScan for the early diagnosis of dementia in patients with and without a clinical vascular component, and the association between neuropsychological function, vascular component and dopaminergic function on DaTScan. One-hundred and five patients with MCI or the initial phases of dementia were studied prospectively. We developed an initial assessment using neurologic examination, blood tests, cognitive function tests, structural neuroimaging and DaTScan. The vascular component was later quantified in two ways: clinically, according to the Framingham Risk Score (FRS) and by structural neuroimaging using Wahlund Scale Total Score (WSTS). Early diagnosis of dementia was associated with an abnormal DaTScan. A significant association was found between a high WSTS and an abnormal DaTScan (p < 0.01). Mixed AD was the group with the highest vascular component, followed by the VaD group, while MCI and pure AD showed similar WSTS. No significant associations were found between neuropsychological impairment and DaTScan independently of associated vascular component. DaTScan seems to be a good tool to discriminate, in a first clinical assessment, patients with MCI from those with established dementia. There was bigger general vascular affectation observable in MRI or CT in patients with abnormal dopaminergic uptake seen on DaTScan.

Dilated perivascular spaces in the Basal Ganglia are a biomarker of small-vessel disease in a very elderly population with dementia

BACKGROUND AND PURPOSE

Dilated perivascular spaces have been shown to be a specific biomarker of cerebral small-vessel disease in young patients with dementia. Our aim was to examine the discriminative power of dilated cerebral perivascular spaces as biomarkers of small-vessel disease in a very elderly population of patients with dementia.

MATERIALS AND METHODS

We studied healthy volunteers (n = 65; mean age, 78 ± 5.6 years) and subjects with vascular dementia (n = 39; mean age, 76.9 ± 7.7 years) and Alzheimer disease (n = 47; mean age, 74.1 ± 8.5 years). We compared white matter hyperintensity and 2 semiquantitative perivascular space scoring systems (perivascular space-1 and perivascular space-2). Intra- and interobserver agreement was assessed by using a weighted Cohen κ statistic. Multinomial regression modeling was used to assess the discriminative power of imaging features to distinguish clinical groups.

RESULTS

White matter hyperintensity scores were higher in vascular dementia than in Alzheimer disease (P < .05) or healthy volunteers (P < .01). The perivascular space-1 score was higher in vascular dementia and Alzheimer disease than in healthy volunteers (P < .01). The perivascular space-2 score in the centrum semiovale showed no intergroup differences. However, perivascular space-2 in the basal ganglia was higher in vascular dementia than in Alzheimer disease (P < .05) or healthy volunteers (P < .001) and higher in Alzheimer disease than in healthy volunteers (P < .001). Modeling of dementia versus healthy volunteers, Alzheimer disease versus healthy volunteers, and vascular dementia against Alzheimer disease demonstrated perivascular space-2basal ganglia as the only imaging parameter with independent significant discriminative power (P < .01, P < .01, and P < .05) with areas under the receiver operating characteristic curve of 0.855, 0.774, and 0.71, respectively. Modeling of vascular dementia versus healthy volunteers showed that perivascular space-2basal ganglia (P < .01) and the modified Scheltens score (P < .05) contributed significant, independent discriminatory power, accounting for 34% and 13% of the variance in the model respectively.

CONCLUSIONS

Dilated perivascular spaces remain a valuable biomarker of small-vessel disease in an elderly population.

Comprehensive gene expression profiling reveals synergistic functional networks in cerebral vessels after hypertension or hypercholesterolemia

Atherosclerotic stenosis of cerebral arteries or intracranial large artery disease (ICLAD) is a major cause of stroke especially in Asians, Hispanics and Africans, but relatively little is known about gene expression changes in vessels at risk. This study compares comprehensive gene expression profiles in the middle cerebral artery (MCA) of New Zealand White rabbits exposed to two stroke risk factors i.e. hypertension and/or hypercholesterolemia, by the 2-Kidney-1-Clip method, or dietary supplementation with cholesterol. Microarray and Ingenuity Pathway Analyses of the MCA of the hypertensive rabbits showed up-regulated genes in networks containing the node molecules: UBC (ubiquitin), P38 MAPK, ERK, NFkB, SERPINB2, MMP1 and APP (amyloid precursor protein); and down-regulated genes related to MAPK, ERK 1/2, Akt, 26 s proteasome, histone H3 and UBC. The MCA of hypercholesterolemic rabbits showed differentially expressed genes that are surprisingly, linked to almost the same node molecules as the hypertensive rabbits, despite a relatively low percentage of ‘common genes’ (21 and 7%) between the two conditions. Up-regulated common genes were related to: UBC, SERPINB2, TNF, HNF4A (hepatocyte nuclear factor 4A) and APP, and down-regulated genes, related to UBC. Increased HNF4A message and protein were verified in the aorta. Together, these findings reveal similar nodal molecules and gene pathways in cerebral vessels affected by hypertension or hypercholesterolemia, which could be a basis for synergistic action of risk factors in the pathogenesis of ICLAD.

Cerebral blood flow in Alzheimer's disease

Background

Alzheimer’s disease (AD) dementia is a consequence of heterogeneous and complex interactions of age-related neurodegeneration and vascular-associated pathologies. Evidence has accumulated that there is increased atherosclerosis/arteriosclerosis of the intracranial arteries in AD and that this may be additive or synergistic with respect to the generation of hypoxia/ischemia and cognitive dysfunction. The effectiveness of pharmacologic therapies and lifestyle modification in reducing cardiovascular disease has prompted a reconsideration of the roles that cardiovascular disease and cerebrovascular function play in the pathogenesis of dementia.

Methods

Using two-dimensional phase-contrast magnetic resonance imaging, we quantified cerebral blood flow within the internal carotid, basilar, and middle cerebral arteries in a group of individuals with mild to moderate AD (n = 8) and compared the results with those from a group of age-matched nondemented control (NDC) subjects (n = 9). Clinical and psychometric testing was performed on all individuals, as well as obtaining their magnetic resonance imaging-based hippocampal volumes.

Results

Our experiments reveal that total cerebral blood flow was 20% lower in the AD group than in the NDC group, and that these values were directly correlated with pulse pressure and cognitive measures. The AD group had a significantly lower pulse pressure (mean AD 48, mean NDC 71; P = 0.0004). A significant group difference was also observed in their hippocampal volumes. Composite z-scores for clinical, psychometric, hippocampal volume, and hemodynamic data differed between the AD and NDC subjects, with values in the former being significantly lower (t = 12.00, df = 1, P = 0.001) than in the latter.

Conclusion

These results indicate an association between brain hypoperfusion and the dementia of AD. Cardiovascular disease combined with brain hypoperfusion may participate in the pathogenesis/pathophysiology of neurodegenerative diseases. Future longitudinal and larger-scale confirmatory investigations measuring multidomain parameters are warranted.

Diffusion tensor imaging studies in vascular disease: A review of the literature

Cerebrovascular disease (CVD) is often present in old age and may be associated with microstructural pathology of white matter (WM) and cognitive dysfunction. The current review investigated the relationship between CVD, cognitive status and WM integrity as assessed by diffusion tensor imaging (DTI).

Plasma biomarkers of brain atrophy in Alzheimer's disease

Peripheral biomarkers of Alzheimer's disease (AD) reflecting early neuropathological change are critical to the development of treatments for this condition. The most widely used indicator of AD pathology in life at present is neuroimaging evidence of brain atrophy. We therefore performed a proteomic analysis of plasma to derive biomarkers associated with brain atrophy in AD. Using gel based proteomics we previously identified seven plasma proteins that were significantly associated with hippocampal volume in a combined cohort of subjects with AD (N = 27) and MCI (N = 17). In the current report, we validated this finding in a large independent cohort of AD (N = 79), MCI (N = 88) and control (N = 95) subjects using alternative complementary methods—quantitative immunoassays for protein concentrations and estimation of pathology by whole brain volume. We confirmed that plasma concentrations of five proteins, together with age and sex, explained more than 35% of variance in whole brain volume in AD patients. These proteins are complement components C3 and C3a, complement factor-I, γ-fibrinogen and alpha-1-microglobulin. Our findings suggest that these plasma proteins are strong predictors of in vivo AD pathology. Moreover, these proteins are involved in complement activation and coagulation, providing further evidence for an intrinsic role of these pathways in AD pathogenesis.

Assessment of the Virchow-Robin Spaces in Alzheimer disease, mild cognitive impairment, and normal aging, using high-field MR imaging

BACKGROUND AND PURPOSE

VRSs are the perivascular spaces surrounding the deep perforating arteries in the brain. Although VRS variations with age and disease pathologies have been reported previously, the radiologic characteristics of the VRS in relation to AD are poorly understood. This study investigated the prevalence, spatial distribution, and severity of the VRS in AD, MCI, and older adults who were CN. It also investigated the relationship of the VRS to white matter changes.

MATERIALS AND METHODS

Structural MR imaging data were acquired from 158 participants (AD = 37, MCI = 71, CN = 50, mean age = 74.97 ± 7.20 years) who had undergone T1WI at 3T. The severity of VRS in the white matter, basal ganglia, hippocampus, and brain stem structures was evaluated by using a semiquantitative scale, adapted from existing rating scales. A VRS total score summarizing the subscales was calculated to assess the whole-brain VRSs.

RESULTS

VRSs were observed in multiple brain regions of all participants, typically presented as <2-mm well-margined symmetric round-, oval- and linear-shaped hypointensities on T1WI. The VRS total score increased with leukoaraiosis, atrophy, and advanced age (P < .001). Individuals with AD and MCI showed greater levels of VRS than control subjects. The VRS total score discriminated individuals with AD and those who were CN with an accuracy of 0.79 (95% CI, 0.69-0.89).

CONCLUSIONS

VRSs are common in older adults and are more severe in AD and MCI than in CN. Whether increased VRSs can be reliably used to aid in AD diagnosis warrants further investigation.

Magnetic resonance imaging-measured atrophy and its relationship to cognitive functioning in vascular dementia and Alzheimer's disease patients

BACKGROUND

Recent pathological studies report vascular pathology in clinically diagnosed Alzheimer's disease (AD) and AD pathology in clinically diagnosed vascular dementia (VaD). We compared magnetic resonance imaging (MRI) measures of vascular brain injury (white matter hyperintensities [WMH] and infarcts) with neurodegenerative measures (medial-temporal atrophy [MTA] and cerebral atrophy [CA]) in clinically diagnosed subjects with either AD or VaD. We then examined relationships among these measures within and between the two groups and their relationship to mental status.

METHODS

Semi-quantitative MRI measures were derived from blind ratings of MRI scans obtained from participants in a research clinical trial of VaD (N = 694) and a genetic epidemiological study of AD (N = 655).

RESULTS

CA was similar in the two groups, but differences in the mean of MTA and WMH were pronounced. Infarcts were significantly associated with CA in VaD but not in AD; MTA and WMH were associated with CA in both. WMH was associated with MTA in both groups; however, MRI infarcts were associated with MTA in VaD but not with MTA in AD patients. MTA was strongly associated with Mini-Mental State Examination scores in both groups, whereas evidence of a modest association between WMH and Mini-Mental State Examination scores was seen in VaD patients.

CONCLUSIONS

MRI data from two dementia cohorts with differing dementia etiologies find that the clinical consequences of dementia are most strongly associated with cerebral and medial-temporal atrophy, suggesting that tissue loss is the major substrate of the dementia syndrome.

Serial susceptibility weighted MRI measures brain iron and microbleeds in dementia

A new iron sensitive MR sequence (susceptibility weighted imaging - SWI) enabling the simultaneous quantitation of regional brain iron levels and brain microbleeds (BMB) has been acquired serially to study dementia. Cohorts of mildly cognitively impaired (MCI) elderly (n = 73) and cognitively normal participants (n = 33) have been serially evaluated for up to 50 months. SWI phase values (putative iron levels) in 14 brain regions were measured and the number of BMB were counted for each SWI study. SWI phase values showed a left putaminal mean increase of iron (decrease of phase values) over the study duration in 27 participants who progressed to dementia compared to Normals (p = 0.035) and stable MCI (p = 0.01). BMB were detected in 9 out of 26 (38%) MCI participants who progressed to dementia and are a significant risk factor for cognitive failure in MCI participants [risk ratio = 2.06 (95% confidence interval 1.37-3.12)]. SWI is useful to measure regional iron changes and presence of BMB, both of which may be important MR-based biomarkers for neurodegenerative diseases.

Orthostatic hypotension and cognitive function: the Atherosclerosis Risk in Communities Study

BACKGROUND

To examine the association between orthostatic hypotension (OH) and cognitive function in middle-aged adults.

METHODS

Participants were 12,702 men and women from the Atherosclerosis Risk in Communities Study. OH was defined as decrease in systolic blood pressure (BP) by > or =20 mm Hg or diastolic BP by > or =10 mm Hg upon standing. At the 2nd and the 4th follow-up examinations, cognitive function was assessed using the Delayed Word Recall Test, Digit Symbol Substitution Test (DSST) and Word Fluency Test (WFT).

RESULTS

After age adjustment, those with OH were more likely to be in the lowest quintile of the DSST (OR = 1.34, 95% CI = 1.12-1.62) and WFT (OR = 1.25, 95% CI = 1.03-1.51) than were those without OH. After adjustment for sociodemographic and cardiovascular risk factors, associations were no longer significant. In age-adjusted models only, OH was associated with increased odds of being in the greatest quintile of decline in DSST score between visits 2 and 4 (OR = 1.28, 95% CI = 1.04-1.58).

CONCLUSIONS

OH was associated with less favorable cognitive function, but this association was largely attributable to demographic and cardiovascular risk factors. Episodic asymptomatic hypotension in middle age may not be an independent cause of cognitive decline. Further study, including emphasis on neuroimaging, is needed.

Blood-based biomarkers of microvascular pathology in Alzheimer's disease

Sporadic Alzheimer's disease (AD) is a genetically complex and chronically progressive neurodegenerative disorder with molecular mechanisms and neuropathologies centering around the amyloidogenic pathway, hyperphosphorylation and aggregation of tau protein, and neurofibrillary degeneration. While cerebrovascular changes have not been traditionally considered to be a central part of AD pathology, a growing body of evidence demonstrates that they may, in fact, be a characteristic feature of the AD brain as well. In particular, microvascular abnormalities within the brain have been associated with pathological AD hallmarks and may precede neurodegeneration. In vivo assessment of microvascular pathology provides a promising approach to develop useful biological markers for early detection and pathological characterization of AD. This review focuses on established blood-based biological marker candidates of microvascular pathology in AD. These candidates include plasma concentration of vascular cell adhesion molecule-1 (VCAM-1) and intercellular adhesion molecule-1 (ICAM-1) that are increased in AD. Measures of endothelial vasodilatory function including endothelin (ET-1), adrenomedullin (ADM), and atrial natriuretic peptide (ANP), as well as sphingolipids are significantly altered in mild AD or during the predementia stage of mild cognitive impairment (MCI), suggesting sensitivity of these biomarkers for early detection and diagnosis. In conclusion, the emerging clinical diagnostic evidence for the value of blood-based microvascular biomarkers in AD is promising, however, still requires validation in phase II and III diagnostic trials. Moreover, it is still unclear whether the described protein dysbalances are early or downstream pathological events and how the detected systemic microvascular alterations relate to cerebrovascular and neuronal pathologies in the AD brain.