Changes in premorbid brain volume predict Alzheimer's disease pathology

Neuroprotective potentials of Lead phytochemicals against Alzheimer's disease with focus on oxidative stress-mediated signaling pathways: Pharmacokinetic challenges, target specificity, clinical trials and future perspectives

BACKGROUND

Alzheimer's diseases (AD) and dementia are among the highly prevalent neurological disorders characterized by deposition of beta amyloid (Aβ) plaques, dense deposits of highly phosphorylated tau proteins, insufficiency of acetylcholine (ACh) and imbalance in glutamatergic system. Patients typically experience cognitive, behavioral alterations and are unable to perform their routine activities. Evidence also suggests that inflammatory processes including excessive microglia activation, high expression of inflammatory cytokines and release of free radicals. Thus, targeting inflammatory pathways beside other targets might be the key factors to control- disease symptoms and progression.

PURPOSE

This review is aimed to highlight the mechanisms and pathways involved in the neuroprotective potentials of lead phytochemicals. Further to provide updates regarding challenges associated with their use and their progress into clinical trials as potential lead compounds.

METHODS

Most recent scientific literature on pre-clinical and clinical data published in quality journals especially on the lead phytochemicals including curcumin, catechins, quercetin, resveratrol, genistein and apigenin was collected using SciFinder, PubMed, Google Scholar, Web of Science, JSTOR, EBSCO, Scopus and other related web sources.

RESULTS

Literature review indicated that the drug discovery against AD is insufficient and only few drugs are clinically approved which have limited efficacy. Among the therapeutic options, natural products have got tremendous attraction owing to their molecular diversity, their safety and efficacy. Research suggest that natural products can delay the disease onset, reduce its progression and regenerate the damage via their anti-amyloid, anti-inflammatory and antioxidant potentials. These agents regulate the pathways involved in the release of neurotrophins which are implicated in neuronal survival and function. Highly potential lead phytochemicals including curcumin, catechins, quercetin, resveratrol, genistein and apigenin regulate neuroprotective signaling pathways implicated in neurotrophins-mediated activation of tropomyosin receptor kinase (Trk) and p75 neurotrophins receptor (p75NTR) family receptors.

CONCLUSIONS

Phytochemicals especially phenolic compounds were identified as highly potential molecules which ameliorate oxidative stress induced neurodegeneration, reduce Aβ load and inhibit vital enzymes. Yet their clinical efficacy and bioavailability are the major challenges which need further interventions for more effective therapeutic outcomes.

A pilot study to evaluate the effect of CT1812 treatment on synaptic density and other biomarkers in Alzheimer's disease

BACKGROUND

Effective, disease-modifying therapeutics for the treatment of Alzheimer's disease (AD) remain a large unmet need. Extensive evidence suggests that amyloid beta (Aβ) is central to AD pathophysiology, and Aβ oligomers are among the most toxic forms of Aβ. CT1812 is a novel brain penetrant sigma-2 receptor ligand that interferes with the binding of Aβ oligomers to neurons. Preclinical studies of CT1812 have demonstrated its ability to displace Aβ oligomers from neurons, restore synapses in cell cultures, and improve cognitive measures in mouse models of AD. CT1812 was found to be generally safe and well tolerated in a placebo-controlled phase 1 clinical trial in healthy volunteers and phase 1a/2 clinical trials in patients with mild to moderate dementia due to AD. The unique objective of this study was to incorporate synaptic positron emission tomography (PET) imaging as an outcome measure for CT1812 in AD patients.

METHODS

The present phase 1/2 study was a randomized, double-blind, placebo-controlled, parallel-group trial conducted in 23 participants with mild to moderate dementia due to AD to primarily evaluate the safety of CT1812 and secondarily its pharmacodynamic effects. Participants received either placebo or 100 mg or 300 mg per day of oral CT1812 for 24 weeks. Pharmacodynamic effects were assessed using the exploratory efficacy endpoints synaptic vesicle glycoprotein 2A (SV2A) PET, fluorodeoxyglucose (FDG) PET, volumetric MRI, cognitive clinical measures, as well as cerebrospinal fluid (CSF) biomarkers of AD pathology and synaptic degeneration.

RESULTS

No treatment differences relative to placebo were observed in the change from baseline at 24 weeks in either SV2A or FDG PET signal, the cognitive clinical rating scales, or in CSF biomarkers. Composite region volumetric MRI revealed a trend towards tissue preservation in participants treated with either dose of CT1812, and nominally significant differences with both doses of CT1812 compared to placebo were found in the pericentral, prefrontal, and hippocampal cortices. CT1812 was safe and well tolerated.

CONCLUSIONS

The safety findings of this 24-week study and the observed changes on volumetric MRI with CT1812 support its further clinical development.

TRIAL REGISTRATION

The clinical trial described in this manuscript is registered at clinicaltrials.gov (NCT03493282).

A deep neural network estimation of brain age is sensitive to cognitive impairment and decline

The greatest known risk factor for Alzheimer's disease (AD) is age. While both normal aging and AD pathology involve structural changes in the brain, their trajectories of atrophy are not the same. Recent developments in artificial intelligence have encouraged studies to leverage neuroimaging-derived measures and deep learning approaches to predict brain age, which has shown promise as a sensitive biomarker in diagnosing and monitoring AD. However, prior efforts primarily involved structural magnetic resonance imaging and conventional diffusion MRI (dMRI) metrics without accounting for partial volume effects. To address this issue, we post-processed our dMRI scans with an advanced free-water (FW) correction technique to compute distinct FW-corrected fractional anisotropy (FAFWcorr) and FW maps that allow for the separation of tissue from fluid in a scan. We built 3 densely connected neural networks from FW-corrected dMRI, T1-weighted MRI, and combined FW+T1 features, respectively, to predict brain age. We then investigated the relationship of actual age and predicted brain ages with cognition. We found that all models accurately predicted actual age in cognitively unimpaired (CU) controls (FW: r=0.66, p=1.62×10-32; T1: r=0.61, p=1.45×10-26, FW+T1: r=0.77, p=6.48×10-50) and distinguished between CU and mild cognitive impairment participants (FW: p=0.006; T1: p=0.048; FW+T1: p=0.003), with FW+T1-derived age showing best performance. Additionally, all predicted brain age models were significantly associated with cross-sectional cognition (memory, FW: β=-1.094, p=6.32×10-7; T1: β=-1.331, p=6.52×10-7; FW+T1: β=-1.476, p=2.53×10-10; executive function, FW: β=-1.276, p=1.46×10-9; T1: β=-1.337, p=2.52×10-7; FW+T1: β=-1.850, p=3.85×10-17) and longitudinal cognition (memory, FW: β=-0.091, p=4.62×10-11; T1: β=-0.097, p=1.40×10-8; FW+T1: β=-0.101, p=1.35×10-11; executive function, FW: β=-0.125, p=1.20×10-10; T1: β=-0.163, p=4.25×10-12; FW+T1: β=-0.158, p=1.65×10-14). Our findings provide evidence that both T1-weighted MRI and dMRI measures improve brain age prediction and support predicted brain age as a sensitive biomarker of cognition and cognitive decline.

Association between pseudoexfoliation and Alzheimer's disease-related brain atrophy

BACKGROUND/AIMS

Pseudoexfoliation (PEX) syndrome is an age-related disorder characterized by the accumulation of extracellular material in the anterior eye segment. PEX pathogenesis is not fully understood, but amyloid which accumulates in the brain of patients with Alzheimer's disease (AD) is a PEX component. PEX deposition shares features with amyloid aggregation in AD, and brain atrophy is a common AD feature, with β-amyloid accumulation among contributing factors. This study investigated whether PEX syndrome is associated with AD-related brain atrophy.

METHODS

We reviewed the medical records of patients diagnosed with PEX at the Veterans Health Service Medical Center between January 2015 and August 2021. This retrospective cohort study included 48 patients with PEX and 48 healthy age- and sex-matched controls. Patients with PEX were divided into two groups: with and without glaucoma. The main outcome measure was brain atrophy, using a visual rating scale, and AD incidence. Brain atrophy was measured using the Scheltens scale for medial temporal atrophy, the posterior cortical atrophy scale for parietal atrophy, and the Pasquier scale for global cortical atrophy.

RESULTS

The percentage of participants with medial temporal atrophy was 56.3% in the PEX group and 35.4% in the control group. The global cortical atrophy and parietal atrophy scores were significantly higher in the PEX group (P<0.05), whereas the PEX and PEX glaucoma groups showed no difference. Among the 96 participants, 16 and 5 participants in the PEX and control groups, respectively, were diagnosed with dementia. Patients with PEX glaucoma tended to have lower Mini-Mental State Examination scores, indicating impaired cognitive function, than those without glaucoma.

CONCLUSION

PEX is associated with brain atrophy, reflecting the risk of developing AD. Patients with PEX glaucoma may present with advanced AD stages. Our results suggest that PEX may be a predictor of AD.

Decoding the heterogeneity of Alzheimer's disease diagnosis and progression using multilayer networks

Alzheimer's disease (AD) is a multifactorial and heterogeneous disorder, which makes early detection a challenge. Studies have attempted to combine biomarkers to improve AD detection and predict progression. However, most of the existing work reports results in parallel or compares normalized findings but does not analyze data simultaneously. We tested a multi-dimensional network framework, applied to 490 subjects (cognitively normal [CN] = 147; mild cognitive impairment [MCI] = 287; AD = 56) from ADNI, to create a single model capable of capturing the heterogeneity and progression of AD. First, we constructed subject similarity networks for structural magnetic resonance imaging, amyloid-β positron emission tomography, cerebrospinal fluid, cognition, and genetics data and then applied multilayer community detection to find groups with shared similarities across modalities. Individuals were also followed-up longitudinally, with AD subjects having, on average, 4.5 years of follow-up. Our findings show that multilayer community detection allows for accurate identification of present and future AD (≈90%) and is also able to identify cases that were misdiagnosed clinically. From all MCI participants who developed AD or reverted to CN, the multilayer model correctly identified 90.8% and 88.5% of cases respectively. We observed similar subtypes across the full sample and when examining multimodal data from subjects with no AD pathology (i.e., amyloid negative). Finally, these results were also validated using an independent testing set. In summary, the multilayer framework is successful in detecting AD and provides unique insight into the heterogeneity of the disease by identifying subtypes that share similar multidisciplinary profiles of neurological, cognitive, pathological, and genetics information.

Comparison of Structural Changes in Nodding Syndrome and Other Epilepsies Associated With Onchocerca volvulus

BACKGROUND AND OBJECTIVE

Nodding syndrome (NS) is a unique childhood-onset epileptic disorder that occurs predominantly in several regions of sub-Saharan Africa. The disease has been associated with Onchocerca volvulus (Ov)-induced immune responses and possible cross-reactivity with host proteins. The aim of this study was to compare structural changes in the brain on MRI between NS and other forms of onchocerciasis-associated epilepsies (OAEs) and to relate structural changes to the Ov-induced immune responses and level of disability.

METHODS

Thirty-nine children with NS and 14 age-matched participants with other forms of OAE from an endemic region in Uganda underwent detailed clinical examination, serologic evaluation (including Ov-associated antibodies to Ov-16 and Hu-leiomodin-1) and quantitative volumetric analysis of brain MRIs (1.5 T scanner) using Neuroreader, a cloud-based software.

RESULTS

Cerebral and cerebellar atrophy were the predominant features in both NS and OAE. On quantitative volumetric analysis, participants with NS had larger ventricular volumes compared with participants with OAE, indicative of increased global cortical atrophy (p_corr = 0.036). Among children with NS, severe disability correlated with higher degree of atrophy in the gray matter volume (p_corr = 0.009) and cerebellar volume (p_corr = 0.009). NS cases had lower anti-Ov-16 IgG signal-to-noise ratios than the OAE cases (p < 0.01), but no difference in the levels of the Hu-leiomodin-1 antibodies (p = 0.64). The levels of Ov-associated antibodies did not relate to the degree of cerebral or cerebellar atrophy in either NS or OAE cases.

DISCUSSION

This is the first study to show that cerebral and cerebellar atrophy correlated with the severity of NS disability, providing an imaging marker for these endemic epileptic disorders that until now have remained poorly characterized. Both NS and OAE have cerebral and cerebellar atrophy, and the levels of Ov-associated antibodies do not seem to be related to the structural changes on MRI.

Identifying the regional substrates predictive of Alzheimer's disease progression through a convolutional neural network model and occlusion

Progressive brain atrophy is a key neuropathological hallmark of Alzheimer's disease (AD) dementia. However, atrophy patterns along the progression of AD dementia are diffuse and variable and are often missed by univariate methods. Consequently, identifying the major regional atrophy patterns underlying AD dementia progression is challenging. In the current study, we propose a method that evaluates the degree to which specific regional atrophy patterns are predictive of AD dementia progression, while holding all other atrophy changes constant using a total sample of 334 subjects. We first trained a dense convolutional neural network model to differentiate individuals with mild cognitive impairment (MCI) who progress to AD dementia versus those with a stable MCI diagnosis. Then, we retested the model multiple times, each time occluding different regions of interest (ROIs) from the model's testing set's input. We also validated this approach by occluding ROIs based on Braak's staging scheme. We found that the hippocampus, fusiform, and inferior temporal gyri were the strongest predictors of AD dementia progression, in agreement with established staging models. We also found that occlusion of limbic ROIs defined according to Braak stage III had the largest impact on the performance of the model. Our predictive model reveals the major regional patterns of atrophy predictive of AD dementia progression. These results highlight the potential for early diagnosis and stratification of individuals with prodromal AD dementia based on patterns of cortical atrophy, prior to interventional clinical trials.

Perivascular spaces as a potential biomarker of Alzheimer's disease

Alzheimer's disease (AD) is a highly damaging disease that affects one's cognition and memory and presents an increasing societal and economic burden globally. Considerable research has gone into understanding AD; however, there is still a lack of effective biomarkers that aid in early diagnosis and intervention. The recent discovery of the glymphatic system and associated Perivascular Spaces (PVS) has led to the theory that enlarged PVS (ePVS) may be an indicator of AD progression and act as an early diagnostic marker. Visible on Magnetic Resonance Imaging (MRI), PVS appear to enlarge when known biomarkers of AD, amyloid-β and tau, accumulate. The central goal of ePVS and AD research is to determine when ePVS occurs in AD progression and if ePVS are causal or epiphenomena. Furthermore, if ePVS are indeed causative, interventions promoting glymphatic clearance are an attractive target for research. However, it is necessary first to ascertain where on the pathological progression of AD ePVS occurs. This review aims to examine the knowledge gap that exists in understanding the contribution of ePVS to AD. It is essential to understand whether ePVS in the brain correlate with increased regional tau distribution and global or regional Amyloid-β distribution and to determine if these spaces increase proportionally over time as individuals experience neurodegeneration. This review demonstrates that ePVS are associated with reduced glymphatic clearance and that this reduced clearance is associated with an increase in amyloid-β. However, it is not yet understood if ePVS are the outcome or driver of protein accumulation. Further, it is not yet clear if ePVS volume and number change longitudinally. Ultimately, it is vital to determine early diagnostic criteria and early interventions for AD to ease the burden it presents to the world; ePVS may be able to fulfill this role and therefore merit further research.

Neuroimaging Modalities in Alzheimer’s Disease: Diagnosis and Clinical Features

Alzheimer’s disease (AD) is a neurodegenerative disease causing progressive cognitive decline until eventual death. AD affects millions of individuals worldwide in the absence of effective treatment options, and its clinical causes are still uncertain. The onset of dementia symptoms indicates severe neurodegeneration has already taken place. Therefore, AD diagnosis at an early stage is essential as it results in more effective therapy to slow its progression. The current clinical diagnosis of AD relies on mental examinations and brain imaging to determine whether patients meet diagnostic criteria, and biomedical research focuses on finding associated biomarkers by using neuroimaging techniques. Multiple clinical brain imaging modalities emerged as potential techniques to study AD, showing a range of capacity in their preciseness to identify the disease. This review presents the advantages and limitations of brain imaging modalities for AD diagnosis and discusses their clinical value.

Endogenous and Exogenous Estrogen Exposures: How Women's Reproductive Health Can Drive Brain Aging and Inform Alzheimer's Prevention

After advanced age, female sex is the major risk factor for late-onset Alzheimer's disease (AD), the most common cause of dementia affecting over 24 million people worldwide. The prevalence of AD is higher in women than in men, with postmenopausal women accounting for over 60% of all those affected. While most research has focused on gender-combined risk, emerging data indicate sex and gender differences in AD pathophysiology, onset, and progression, which may help account for the higher prevalence in women. Notably, AD-related brain changes develop during a 10-20 year prodromal phase originating in midlife, thus proximate with the hormonal transitions of endocrine aging characteristic of the menopause transition in women. Preclinical evidence for neuroprotective effects of gonadal sex steroid hormones, especially 17β-estradiol, strongly argue for associations between female fertility, reproductive history, and AD risk. The level of gonadal hormones to which the female brain is exposed changes considerably across the lifespan, with relevance to AD risk. However, the neurobiological consequences of hormonal fluctuations, as well as that of hormone therapies, are yet to be fully understood. Epidemiological studies have yielded contrasting results of protective, deleterious and null effects of estrogen exposure on dementia risk. In contrast, brain imaging studies provide encouraging evidence for positive associations between greater cumulative lifetime estrogen exposure and lower AD risk in women, whereas estrogen deprivation is associated with negative consequences on brain structure, function, and biochemistry. Herein, we review the existing literature and evaluate the strength of observed associations between female-specific reproductive health factors and AD risk in women, with a focus on the role of endogenous and exogenous estrogen exposures as a key underlying mechanism. Chief among these variables are reproductive lifespan, menopause status, type of menopause (spontaneous vs. induced), number of pregnancies, and exposure to hormonal therapy, including hormonal contraceptives, hormonal therapy for menopause, and anti-estrogen treatment. As aging is the greatest risk factor for AD followed by female sex, understanding sex-specific biological pathways through which reproductive history modulates brain aging is crucial to inform preventative and therapeutic strategies for AD.

Dementia is associated with medial temporal atrophy even after accounting for neuropathologies

Brain atrophy is associated with degenerative neuropathologies and the clinical status of dementia. Whether dementia is associated with atrophy independent of neuropathologies is not known. In this study, we examined the pattern of atrophy associated with dementia while accounting for the most common dementia-related neuropathologies. We used data from National Alzheimer's Coordinating Center (n = 129) and Alzheimer's Disease Neuroimaging Initiative (n = 47) participants with suitable in vivo 3D-T1w MRI and autopsy data. We determined dementia status at the visit closest to MRI. We examined the following dichotomized neuropathological variables: Alzheimer's disease neuropathology, hippocampal sclerosis, Lewy bodies, cerebral amyloid angiopathy and atherosclerosis. Voxel-based morphometry identified areas associated with dementia after accounting for neuropathologies. Identified regions of interest were further analysed. We used multiple linear regression models adjusted for neuropathologies and demographic variables. We also examined models with dementia and Clinical Dementia Rating sum of the boxes as the outcome and explored the potential mediating effect of medial temporal lobe structure volumes on the relationship between pathology and cognition. We found strong associations for dementia with volumes of the hippocampus, amygdala and parahippocampus (semi-partial correlations ≥ 0.28, P < 0.0001 for all regions in National Alzheimer's Coordinating Center; semi-partial correlations ≥ 0.35, P ≤ 0.01 for hippocampus and parahippocampus in Alzheimer's Disease Neuroimaging Initiative). Dementia status accounted for more unique variance in atrophy in these structures (∼8%) compared with neuropathological variables; the only exception was hippocampal sclerosis which accounted for more variance in hippocampal atrophy (10%). We also found that the volumes of the medial temporal lobe structures contributed towards explaining the variance in Clinical Dementia Rating sum of the boxes (ranging from 5% to 9%) independent of neuropathologies and partially mediated the association between Alzheimer's disease neuropathology and cognition. Even after accounting for the most common neuropathologies, dementia still had among the strongest associations with atrophy of medial temporal lobe structures. This suggests that atrophy of the medial temporal lobe is most related to the clinical status of dementia rather than Alzheimer's disease or other neuropathologies, with the potential exception of hippocampal sclerosis.

Imaging biomarkers for Alzheimer's disease and glaucoma: Current and future practices

Glaucoma is a leading cause of blindness worldwide. Although intraocular pressure is the main risk factor for glaucoma, several intraocular pressure independent factors have been associated with the risk of developing the disease and its progression. The diagnosis of glaucoma relies on clinical features of the optic nerve, visual field test, and optical coherence tomography. However, the multidisciplinary aspect of the disease suggests that other biomarkers may be useful for the diagnosis, thus underling the importance of novel imaging techniques supporting clinicians. This review analyzes the common pathogenic mechanisms between glaucoma and Alzheimer's disease and the possible novel approaches for diagnosis and follow up.

Alzheimer's Disease, Sleep Disordered Breathing, and Microglia: Puzzling out a Common Link

Sleep Disordered Breathing (SDB) and Alzheimer's Disease (AD) are strongly associated clinically, but it is unknown if they are mechanistically associated. Here, we review data covering both the cellular and molecular responses in SDB and AD with an emphasis on the overlapping neuroimmune responses in both diseases. We extensively discuss the use of animal models of both diseases and their relative utilities in modeling human disease. Data presented here from mice exposed to intermittent hypoxia indicate that microglia become more activated following exposure to hypoxia. This also supports the idea that intermittent hypoxia can activate the neuroimmune system in a manner like that seen in AD. Finally, we highlight similarities in the cellular and neuroimmune responses between SDB and AD and propose that these similarities may lead to a pathological synergy between SDB and AD.

Cognitive Dysfunction after Heart Disease: A Manifestation of the Heart-Brain Axis

The functions of the brain and heart, which are the two main supporting organs of human life, are closely linked. Numerous studies have expounded the mechanisms of the brain-heart axis and its related clinical applications. However, the effect of heart disease on brain function, defined as the heart-brain axis, is less studied even though cognitive dysfunction after heart disease is one of its most frequently reported manifestations. Hypoperfusion caused by heart failure appears to be an important risk factor for cognitive decline. Blood perfusion, the immune response, and oxidative stress are the possible main mechanisms of cognitive dysfunction, indicating that the blood-brain barrier, glial cells, and amyloid-β may play active roles in these mechanisms. Clinicians should pay more attention to the cognitive function of patients with heart disease, especially those with heart failure. In addition, further research elucidating the associated mechanisms would help discover new therapeutic targets to intervene in the process of cognitive dysfunction after heart disease. This review discusses cognitive dysfunction in relation to heart disease and its potential mechanisms.

Ocimum sanctum Linn. Extract Improves Cognitive Deficits in Olfactory Bulbectomized Mice via the Enhancement of Central Cholinergic Systems and VEGF Expression

This study aimed to clarify the antidementia effects of ethanolic extract of Ocimum sanctum Linn. (OS) and its underlying mechanisms using olfactory bulbectomized (OBX) mice. OBX mice were treated daily with OS or a reference drug, donepezil (DNP). Spatial and nonspatial working memory performance was measured using a modified Y maze test and a novel object recognition test, respectively. Brain tissues of the animals were subjected to histochemical and neurochemical analysis. OS treatment attenuated OBX-induced impairment of spatial and nonspatial working memories. OBX induced degeneration of septal cholinergic neurons, enlargement of the lateral ventricles, and suppression of hippocampal neurogenesis. OS and DNP treatment also depressed these histological damages. OS administration reduced ex vivo activity of acetylcholinesterase in the brain. OBX diminished the expression levels of genes coding vascular endothelial growth factor (VEGF) and VEGF receptor type 2 (VEGFR2). Treatment with OS and DNP reversed OBX-induced decrease in VEGF gene and protein expression levels without affecting the expression of the VEGFR2 gene. These results demonstrate that the administration of OS can lessen the cognitive deficits and neurohistological damages of OBX and that these actions are, at least in part, mediated by the enhancement of central cholinergic systems and VEGF expression.

Structural volume and cortical thickness differences between males and females in cognitively normal, cognitively impaired and Alzheimer's dementia population

We investigated differences due to sex in brain structural volume and cortical thickness in older cognitively normal (N=742), cognitively impaired (MCI; N=540) and Alzheimer's Dementia (AD; N=402) individuals from the ADNI and AIBL datasets (861 Males and 823 Females). General linear models were used to control the effect of relevant covariates including age, intracranial volume, magnetic resonance imaging (MRI) scanner field strength and scanner types. Significant volumetric differences due to sex were observed within different cortical and subcortical regions of the cognitively normal group. The number of significantly different regions was reduced in the MCI group, and no region remained different in the AD group. Cortical thickness was overall thinner in males than females in the cognitively normal group, and likewise, the differences due to sex were reduced in the MCI and AD groups. These findings were sustained after including cerebrospinal fluid (CSF) Tau and phosphorylated tau (pTau) as additional covariates.

Reduced parenchymal cerebral blood flow is associated with greater progression of brain atrophy: The SMART-MR study

Global cerebral hypoperfusion may be involved in the aetiology of brain atrophy; however, long-term longitudinal studies on this relationship are lacking. We examined whether reduced cerebral blood flow was associated with greater progression of brain atrophy. Data of 1165 patients (61 ± 10 years) from the SMART-MR study, a prospective cohort study of patients with arterial disease, were used of whom 689 participated after 4 years and 297 again after 12 years. Attrition was substantial. Total brain volume and total cerebral blood flow were obtained from magnetic resonance imaging scans and expressed as brain parenchymal fraction (BPF) and parenchymal cerebral blood flow (pCBF). Mean decrease in BPF per year was 0.22% total intracranial volume (95% CI: -0.23 to -0.21). Mean decrease in pCBF per year was 0.24 ml/min per 100 ml brain volume (95% CI: -0.29 to -0.20). Using linear mixed models, lower pCBF at baseline was associated with a greater decrease in BPF over time (p = 0.01). Lower baseline BPF, however, was not associated with a greater decrease in pCBF (p = 0.43). These findings indicate that reduced cerebral blood flow is associated with greater progression of brain atrophy and provide further support for a role of cerebral blood flow in the process of neurodegeneration.

Simple Quantitative Indices for the Differentiation of Advanced-Stage Alzheimer's Disease and Other Limbic Tauopathies

BACKGROUND

The differentiation of Alzheimer's disease (AD) from age-related limbic tauopathies (LT), including argyrophilic grain disease (AGD) and senile dementia of the neurofibrillary tangle type (SD-NFT), is often challenging because specific clinical diagnostic criteria have not yet been established. Despite the utility of specific biomarkers evaluating amyloid and tau to detect the AD-related pathophysiological changes, the expense and associated invasiveness preclude their use as first-line diagnostic tools for all demented patients. Therefore, less invasive and costly biomarkers would be valuable in routine clinical practice for the differentiation of AD and LT.

OBJECTIVE

The purpose of this study is to develop a simple reproducible method on magnetic resonance imaging (MRI) that could be adopted in daily clinical practice for the differentiation of AD and other forms of LT.

METHODS

Our newly proposed three quantitative indices and well-known medial temporal atrophy (MTA) score were evaluated using MRI of pathologically-proven advanced-stage 21 AD, 10 AGD, and 2 SD-NFT patients.

RESULTS

Contrary to MTA score, hippocampal angle (HPA), inferior horn area (IHA), and ratio between HPA and IHA (i.e., IHPA index) demonstrated higher diagnostic performance and reproducibility, especially to differentiate advanced-stage AD patients with Braak neurofibrillary tangle stage V/VI from LT patients (the area under the receiver-operating-characteristic curve of 0.83, 089, and 0.91; intraclass correlation coefficients of 0.930, 0.998, and 0.995, respectively).

CONCLUSION

Quantitative indices reflecting hippocampal deformation with ventricular enlargement are useful to differentiate advanced-stage AD from LT. This simple and convenient method could be useful in daily clinical practice.

Neuroimaging in the Oldest-Old: A Review of the Literature

The oldest-old, those 85 years and older, are the fastest growing segment of the population and present with the highest prevalence of dementia. Given the importance of neuroimaging measures to understand aging and dementia, the objective of this study was to review neuroimaging studies performed in oldest-old participants. We used PubMed, Google Scholar, and Web of Science search engines to identify in vivo CT, MRI, and PET neuroimaging studies either performed in the oldest-old or that addressed the oldest-old as a distinct group in analyses. We identified 60 studies and summarized the main group characteristics and findings. Generally, oldest-old participants presented with greater atrophy compared to younger old participants, with most studies reporting a relatively stable constant decline in brain volumes over time. Oldest-old participants with greater global atrophy and atrophy in key brain structures such as the medial temporal lobe were more likely to have dementia or cognitive impairment. The oldest-old presented with a high burden of white matter lesions, which were associated with various lifestyle factors and some cognitive measures. Amyloid burden as assessed by PET, while high in the oldest-old compared to younger age groups, was still predictive of transition from normal to impaired cognition, especially when other adverse neuroimaging measures (atrophy and white matter lesions) were also present. While this review highlights past neuroimaging research in the oldest-old, it also highlights the dearth of studies in this important population. It is imperative to perform more neuroimaging studies in the oldest-old to better understand aging and dementia.

Protein contributions to brain atrophy acceleration in Alzheimer's disease and primary age-related tauopathy

Alzheimer's disease is characterized by the presence of amyloid-β and tau deposition in the brain, hippocampal atrophy and increased rates of hippocampal atrophy over time. Another protein, TAR DNA binding protein 43 (TDP-43) has been identified in up to 75% of cases of Alzheimer's disease. TDP-43, tau and amyloid-β have all been linked to hippocampal atrophy. TDP-43 and tau have also been linked to hippocampal atrophy in cases of primary age-related tauopathy, a pathological entity with features that strongly overlap with those of Alzheimer's disease. At present, it is unclear whether and how TDP-43 and tau are associated with early or late hippocampal atrophy in Alzheimer's disease and primary age-related tauopathy, whether either protein is also associated with faster rates of atrophy of other brain regions and whether there is evidence for protein-associated acceleration/deceleration of atrophy rates. We therefore aimed to model how these proteins, particularly TDP-43, influence non-linear trajectories of hippocampal and neocortical atrophy in Alzheimer's disease and primary age-related tauopathy. In this longitudinal retrospective study, 557 autopsied cases with Alzheimer's disease neuropathological changes with 1638 ante-mortem volumetric head MRI scans spanning 1.0-16.8 years of disease duration prior to death were analysed. TDP-43 and Braak neurofibrillary tangle pathological staging schemes were constructed, and hippocampal and neocortical (inferior temporal and middle frontal) brain volumes determined using longitudinal FreeSurfer. Bayesian bivariate-outcome hierarchical models were utilized to estimate associations between proteins and volume, early rate of atrophy and acceleration in atrophy rates across brain regions. High TDP-43 stage was associated with smaller cross-sectional brain volumes, faster rates of brain atrophy and acceleration of atrophy rates, more than a decade prior to death, with deceleration occurring closer to death. Stronger associations were observed with hippocampus compared to temporal and frontal neocortex. Conversely, low TDP-43 stage was associated with slower early rates but later acceleration. This later acceleration was associated with high Braak neurofibrillary tangle stage. Somewhat similar, but less striking, findings were observed between TDP-43 and neocortical rates. Braak stage appeared to have stronger associations with neocortex compared to TDP-43. The association between TDP-43 and brain atrophy occurred slightly later in time (∼3 years) in cases of primary age-related tauopathy compared to Alzheimer's disease. The results suggest that TDP-43 and tau have different contributions to acceleration and deceleration of brain atrophy rates over time in both Alzheimer's disease and primary age-related tauopathy.

Exercise interventions do not impact brain volume change in older adults: a systematic review and meta-analysis

Exercise interventions have been shown to positively impact cognitive function in older adults, but the mechanisms underlying the neuroprotective effects of exercise on the brain are not well understood. Here, we aimed to synthesize and quantitatively analyze the current literature on exercise interventions and brain volume change in older adults and to examine the impact of key demographic and intervention features as well as study quality. This study was pre-registered with PROSPERO (CRD42018091866). EBSCOhost, Cochrane Library, Embase, and reference lists were searched to identify randomized-controlled trials (RCTs) of exercise interventions for healthy older adults and older adults (60+) with mild cognitive impairment (MCI). A total of 69 effects from 14 studies were pooled and expressed as Hedge's g using a random-effects model. Results indicated that there was no significant difference in brain volume outcomes for older adults that completed an exercise intervention compared to older adults in control groups (g = 0.012, p = 0.728, 95% CI = -0.055, .078). These results were confirmed using multilevel analysis to account for nesting of effects within studies (g = 0.009, p = 0.826, 95% CI = -0.072, 0.090) and using conservative post-hoc models to address possible non-independence of multiple outcome domains and sample nonindependence. No significant heterogeneity was detected, limiting moderator analyses. The implications for future research are discussed.

[LATE: not every dementia is Alzheimer's disease-Discussion of a new disease entity based on a case example : Current status of limbic-predominant age-related TDP-43 encephalopathy (LATE)]

Die limbisch prädominante altersassoziierte TDP-43(Transactivation response(TAR)-DNA-binding protein 43 kDa)-Enzephalopathie (LATE) wurde kürzlich als eigene neuropathologische Entität im Demenzspektrum charakterisiert. Neuropathologische Veränderungen im Sinne von LATE wurden zuvor bereits als Komorbidität der Alzheimer-Krankheit (AD) beschrieben und spätestens seit 2008 auch als ein von der AD unabhängiger autoptischer Befund. Die Konzeptualisierung von LATE rückt nun die pathogenetische Bedeutung von limbischem TDP-43 als alternative oder komorbide Ursache einer der klinischen AD ähnlichen amnestischen Demenz in das Bewusstsein. LATE könnte divergierende klinische und Biomarkerbefunde erklären, bei denen eine ausgeprägte mnestische Störung ohne Amyloid- und Tau-Veränderungen im Sinne einer AD-Pathologie nachweisbar ist. Ob LATE eine eigenständige neuropathologische Entität darstellt oder eine regionale Ausprägung innerhalb des Spektrums der bekannten TDP-43-assoziierten neurodegenerativen Erkrankungen ist aktuell Gegenstand kontroverser Diskussionen. Die weitere, gezielte Erforschung von TDP-43-Proteinopathien ist davon unabhängig ein vielversprechender Forschungsansatz, um Wissenslücken in der Alzheimer- und Demenzforschung zu schließen. So könnte ganz praktisch die Anreicherung eines amnestischen Phänotyps in klinischen Studien zu amyloidzentrierten Therapien durch das erhöhte Risiko limbischer TDP-43-Komorbidität den Nachweis der klinischen Wirksamkeit erschweren. Dieser Artikel stellt den aktuellen Stand der Diskussion zu LATE vor und illustriert das Konzept und daraus abgeleitete klinische Überlegungen an einem Fallbeispiel.

Systematic and Comprehensive Automated Ventricle Segmentation on Ventricle Images of the Elderly Patients: A Retrospective Study

Background and Objective: Ventricle volume is closely related to hydrocephalus, brain atrophy, Alzheimer's, Parkinson's syndrome, and other diseases. To accurately measure the volume of the ventricles for elderly patients, we use deep learning to establish a systematic and comprehensive automated ventricle segmentation framework.

Methods: The study participation included 20 normal elderly people, 20 patients with cerebral atrophy, 64 patients with normal pressure hydrocephalus, and 51 patients with acquired hydrocephalus. Second, get their imaging data through the picture archiving and communication systems (PACS) system. Then use ITK software to manually label participants' ventricular structures. Finally, extract imaging features through machine learning.

Results: This automated ventricle segmentation method can be applied not only to CT and MRI images but also to images with different scan slice thicknesses. More importantly, it produces excellent segmentation results (Dice > 0.9).

Conclusion: This automated ventricle segmentation method has wide applicability and clinical practicability. It can help clinicians find early disease, diagnose disease, understand the patient's disease progression, and evaluate the patient's treatment effect.

Implicating causal brain imaging endophenotypes in Alzheimer's disease using multivariable IWAS and GWAS summary data

Recent evidence suggests the existence of many undiscovered heritable brain phenotypes involved in Alzheimer's Disease (AD) pathogenesis. This finding necessitates methods for the discovery of causal brain changes in AD that integrate Magnetic Resonance Imaging measures and genotypic data. However, existing approaches for causal inference in this setting, such as the univariate Imaging Wide Association Study (UV-IWAS), suffer from inconsistent effect estimation and inflated Type I errors in the presence of genetic pleiotropy, the phenomenon in which a variant affects multiple causal intermediate risk phenotypes. In this study, we implement a multivariate extension to the IWAS model, namely MV-IWAS, to consistently estimate and test for the causal effects of multiple brain imaging endophenotypes from the Alzheimer's Disease Neuroimaging Initiative (ADNI) in the presence of pleiotropic and possibly correlated SNPs. We further extend MV-IWAS to incorporate variant-specific direct effects on AD, analogous to the existing Egger regression Mendelian Randomization approach, which allows for testing of remaining pleiotropy after adjusting for multiple intermediate pathways. We propose a convenient approach for implementing MV-IWAS that solely relies on publicly available GWAS summary data and a reference panel. Through simulations with either individual-level or summary data, we demonstrate the well controlled Type I errors and superior power of MV-IWAS over UV-IWAS in the presence of pleiotropic SNPs. We apply the summary statistic based tests to 1578 heritable imaging derived phenotypes (IDPs) from the UK Biobank. MV-IWAS detected numerous IDPs as possible false positives by UV-IWAS while uncovering many additional causal neuroimaging phenotypes in AD which are strongly supported by the existing literature.

Exploring a Cost-Efficient Model for Predicting Cerebral Aβ Burden Using MRI and Neuropsychological Markers in the ADNI-2 Cohort

Many studies have focused on the early detection of Alzheimer’s disease (AD). Cerebral amyloid beta (Aβ) is a hallmark of AD and can be observed in vivo via positron emission tomography imaging using an amyloid tracer or cerebrospinal fluid assessment. However, these methods are expensive. The current study aimed to identify and compare the ability of magnetic resonance imaging (MRI) markers and neuropsychological markers to predict cerebral Aβ status in an AD cohort using machine learning (ML) approaches. The prediction ability of candidate markers for cerebral Aβ status was examined by analyzing 724 participants from the ADNI-2 cohort. Demographic variables, structural MRI markers, and neuropsychological test scores were used as input in several ML algorithms to predict cerebral Aβ positivity. Out of five combinations of candidate markers, neuropsychological markers with demographics showed the most cost-efficient result. The selected model could distinguish abnormal levels of Aβ with a prediction ability of 0.85, which is the same as that for MRI-based models. In this study, we identified the prediction ability of MRI markers using ML approaches and showed that the neuropsychological model with demographics can predict Aβ positivity, suggesting a more cost-efficient method for detecting cerebral Aβ status compared to MRI markers.

Using machine learning to quantify structural MRI neurodegeneration patterns of Alzheimer's disease into dementia score: Independent validation on 8,834 images from ADNI, AIBL, OASIS, and MIRIAD databases

Biomarkers for dementia of Alzheimer's type (DAT) are sought to facilitate accurate prediction of the disease onset, ideally predating the onset of cognitive deterioration. T1-weighted magnetic resonance imaging (MRI) is a commonly used neuroimaging modality for measuring brain structure in vivo, potentially providing information enabling the design of biomarkers for DAT. We propose a novel biomarker using structural MRI volume-based features to compute a similarity score for the individual's structural patterns relative to those observed in the DAT group. We employed ensemble-learning framework that combines structural features in most discriminative ROIs to create an aggregate measure of neurodegeneration in the brain. This classifier is trained on 423 stable normal control (NC) and 330 DAT subjects, where clinical diagnosis is likely to have the highest certainty. Independent validation on 8,834 unseen images from ADNI, AIBL, OASIS, and MIRIAD Alzheimer's disease (AD) databases showed promising potential to predict the development of DAT depending on the time-to-conversion (TTC). Classification performance on stable versus progressive mild cognitive impairment (MCI) groups achieved an AUC of 0.81 for TTC of 6 months and 0.73 for TTC of up to 7 years, achieving state-of-the-art results. The output score, indicating similarity to patterns seen in DAT, provides an intuitive measure of how closely the individual's brain features resemble the DAT group. This score can be used for assessing the presence of AD structural atrophy patterns in normal aging and MCI stages, as well as monitoring the progression of the individual's brain along with the disease course.

Neuropathologic features associated with basal forebrain atrophy in Alzheimer disease

OBJECTIVE

To study the neuropathologic correlates of cholinergic basal forebrain (BF) atrophy as determined using antemortem MRI in the Alzheimer disease (AD) spectrum.

METHODS

We determined associations between BF volume from antemortem MRI brain scans and postmortem assessment of neuropathologic features, including neuritic plaques, neurofibrillary tangles (NFTs), Lewy body (LB) pathology, and TDP-43, in 64 cases of the Alzheimer's Disease Neuroimaging Initiative cohort. For comparison, we assessed neuropathologic features associated with hippocampal and parahippocampal gyrus atrophy. In addition to region of interest-based analysis, we determined the association of neuropathologic features with whole brain gray matter volume using regionally unbiased voxel-based volumetry.

RESULTS

BF atrophy was associated with Thal amyloid phases (95% confidence interval [CI] -0.49 to -0.01, p = 0.049) and presence of LB pathology (95% CI -0.54 to -0.06, p = 0.015), as well as with the degree of LB pathology within the nucleus basalis Meynert (95% CI -0.54 to -0.07, p = 0.025). These effects were no longer significant after false discovery rate (FDR) correction. Hippocampal atrophy was significantly associated with the presence of TDP-43 pathology (95% CI -0.61 to -0.17, p = 0.003; surviving FDR correction), in addition to dentate gyrus NFT load (95% CI -0.49 to -0.01, p = 0.044; uncorrected). Voxel-based analysis confirmed spatially restricted effects of Thal phases and presence of LB pathology on BF volume.

CONCLUSIONS

These findings indicate that neuropathologic correlates of regional atrophy differ substantially between different brain regions that are typically involved in AD-related neurodegeneration, including different susceptibilities to common comorbid pathologies.

Methionine Sulfoxide Reductase-B3 Risk Allele Implicated in Alzheimer's Disease Associates with Increased Odds for Brain Infarcts

Genome-wide association studies identified a single nucleotide polymorphism (SNP) in the MSRB3 gene encoding Methionine Sulfoxide Reductase-B3 (MsrB3) to be associated with the risk for low hippocampal volume and late onset Alzheimer's disease (AD). Subsequently, we identified AD-associated abnormal patterns of neuronal and vascular MsrB3 expression in postmortem hippocampi. The present study investigated the relationship between the MSRB3 SNP rs61921502, G (minor/risk allele) and MRI measures of brain injury including total brain volume, hippocampal volume, and white matter hyperintensities using linear regression models; the presence of brain infarcts using logistic regression models; and the incidence of stroke, dementia, and AD using Cox proportional hazards models in 2,038 Framingham Heart Study Offspring participants with MRI administered close to examination cycle 7 (1998-2001). Participants with neurological conditions that impede evaluation of vascular pathology by MRI, i.e., brain tumors, multiple sclerosis, and major head trauma, were excluded from the study. When adjusted for age and age squared at MRI exam, sex, and presence of Apolipoproteinɛ4 allele (APOE4), individuals with MSRB3 rs61921502 minor allele had increased odds for brain infarcts on MRI compared to those with no minor allele. However, in stratified analyses, MSRB3 rs61921502 minor allele was significantly associated with increased odds for MRI brain infarcts only in the absence of APOE4.

Volume estimation of brain ventricles using Cavalieri's principle and Atlas-based methods in Alzheimer disease: Consistency between methods

Automatic estimations of brain ventricles are needed to assess disease progression in neurodegenerative disorders such as Alzheimer Disease (AD). The objectives of this study are to evaluate the diagnostic performances of an automated volumetric assessment tool in estimating lateral ventricle volumes in AD and to compare this with Cavalieri's principle, which is accepted as the gold standard method. This is across-sectional volumetric study including 25 Alzheimer patients and 25 healthy subjects undergoing magnetic resonance images (MRI) with a 3D turbo spin echo sequence at 1.5 Tesla. The Atlas-based method incorporated MRIStudio software to automatically measure he volumes of brain ventricles. To compare the corresponding measurements, we used manual point-counting and semi-automatic planimetry methods based on Cavalieri's principle. Bland-Altman test results indicated an excellent agreement between Cavalieri's principle and the Atlas-based method in all volumetric measurements (p < 0.05). We obtained a 64% sensitivity and 92% specificity for lateral ventricular volumes according to the Atlas-based method. AD subjects had significantly larger left and right lateral ventricle volume (LVV) when compared to control subjects in respect to three volumetric methods (p < 0.01). Lateral ventricle-to-brain ratio (VBR) statistically increased 49.23% in measurements done with the point-counting method, 45.12% with the planimetry method, and 45.49% with the Atlas-based method in AD patients (p < 0.01). As a result, the Atlas-based method may be used instead of manual volumetry to estimate brain volumes. Additionally, this method provides rapid and accurate estimations of brain ventricular volumes in-vivo examination of MRI.

Effect Modifiers of TDP-43-Associated Hippocampal Atrophy Rates in Patients with Alzheimer's Disease Neuropathological Changes

BACKGROUND

Transactive response DNA-binding protein of 43 kDa (TDP-43) is associated with hippocampal atrophy in Alzheimer's disease (AD), but whether the association is modified by other factors is unknown.

OBJECTIVE

To evaluate whether the associations between TDP-43 and hippocampal volume and atrophy rate are affected by age, gender, apolipoprotein E (APOE) ɛ4, Lewy bodies (LBs), amyloid-β (Aβ), or Braak neurofibrillary tangle (NFT) stage.

METHODS

In this longitudinal neuroimaging-clinicopathological study of 468 cases with AD neuropathological changes (Aβ-positive) that had completed antemortem head MRI, we investigated how age, gender, APOEɛ4, presence of LBs, Aβ, TDP-43, and Braak NFT stages are associated with hippocampal volumes and rates of atrophy over time. We included field strength in the models since our cohort included 1.5T and 3T scans. We then determined whether the associations between hippocampal atrophy and TDP-43 are modified by these factors using mixed effects models.

RESULTS

Older age, female gender, APOEɛ4, higher field strength, higher TDP-43, and Braak NFT stages were associated with smaller hippocampi. Rate of atrophy was greater with higher TDP-43 and Braak NFT stage, but lower in older patients. The association of TDP-43 with greater rate of atrophy was enhanced in APOEɛ4 carriers (p = 0.04).

CONCLUSION

Neurodegenerative effects of TDP-43 seem to be independent of most factors except perhaps APOE in cases with AD neuropathological changes. TDP-43 and tau appear to behave independently of one another.

Braak neurofibrillary tangle staging prediction from in vivo MRI metrics

INTRODUCTION

Alzheimer's disease diagnosis requires postmortem visualization of amyloid and tau deposits. As brain atrophy can provide assessment of consequent neurodegeneration, our objective was to predict postmortem neurofibrillary tangles (NFT) from in vivo MRI measurements.

METHODS

All participants with neuroimaging and neuropathological data from the Alzheimer's Disease Neuroimaging Initiative, the National Alzheimer's Coordinating Center and the Rush Memory and Aging Project were selected (n = 186). Two hundred and thirty two variables were extracted from last MRI before death using FreeSurfer. Nonparametric correlation analysis and multivariable support vector machine classification were performed to provide a predictive model of Braak NFT staging.

RESULTS

We demonstrated that 59 of our MRI variables, mostly temporal lobe structures, were significantly associated with Braak NFT stages (P < .005). We obtained a 62.4% correct classification rate for discrimination between transentorhinal, limbic, and isocortical groups.

DISCUSSION

Structural neuroimaging may therefore be considered as a potential biomarker for early detection of Alzheimer's disease-associated neurofibrillary degeneration.

Association of Apolipoprotein E ε4 With Transactive Response DNA-Binding Protein 43

Importance

Transactive response DNA-binding protein 43 (TDP-43) is associated with Alzheimer disease (AD), progressive hippocampal atrophy, and cognitive decline. The apolipoprotein E (APOE) ε4 allele is strongly associated with β-amyloid (Aβ) aggregation and risk of AD, but its association with TDP-43 is unknown.

Objective

To determine whether the APOE ε4 allele is a risk factor for TDP-43.

Design, Setting, Participants

This cross-sectional, genetic-histologic study analyzed APOE genotype, TDP-43 status (positive vs negative), Aβ status (positive vs negative), and tau neurofibrillary tangle stage (B0, Braak stage 0; B1, Braak stages I-II; B2, Braak stages III-IV; B3, Braak stage ≥ V). We fit structural equation models to map the association between APOE and TDP-43, Aβ, and tau, accounting for age and hippocampal sclerosis. We identified 751 participants with an AD pathological spectrum diagnosis and completed Aβ, tau, and TDP-43 data who were enrolled in the Mayo Clinic Alzheimer Disease Research Center, Mayo Clinic Alzheimer Disease Patient Registry, or the population based Mayo Clinic Study of Aging and died between May 12, 1999, and December 31, 2015. However, 13 were excluded from the analyses because of missing APOE data, leaving a total of 738 participants.

Main Outcomes and Measures

Transactive response DNA-binding protein 43 was the main outcome of interest. We hypothesized that the APOE ε4 allele would be significantly directly and indirectly associated with TDP-43.

Results

The 751 study participants were older (median age [interquartile range], 87 years [51-105 years]), 395 (54%) were women, and 324 (44%) were APOE ε4 carriers. The patients died between May 12, 1999, and December 31, 2015. Accounting for age, Aβ, and tau, APOE ε4 had a direct association with TDP-43 (estimate [SE], 0.31 (0.11); P = .01). The association was present among individuals with an intermediate to high likelihood of having AD (neurofibrillary tangle stage B2/B3; n = 604 [81.8%]; estimate [SE], 0.51 [0.11]; P < .001), with a similar trend for those with a low likelihood of having AD (B1; n = 134 [18.2%]; estimate [SE], 0.54 [0.32]; P = .10). We also found an indirect association of APOE ε4 with TDP-43 via Aβ and tau (estimate [SE], 0.34 [0.06]; P < .001), which was similar in magnitude to the direct association and an indirect association of APOE ε4 with hippocampal sclerosis via TDP-43 (estimate [SE], 0.65 [0.26]; P = .01).

Conclusions and Relevance

The study's findings, which mapped a system of risk factors and outcomes, showed that the APOE ε4 allele appears to be a risk factor for TDP-43 independently of Aβ in patients with AD.

Neuropathologic basis of in vivo cortical atrophy in the aphasic variant of Alzheimer's disease

The neuropathologic basis of in vivo cortical atrophy in clinical dementia syndromes remains poorly understood. This includes primary progressive aphasia (PPA), a language-based dementia syndrome characterized by asymmetric cortical atrophy. The neurofibrillary tangles (NFTs) and amyloid-ß plaques (APs) of Alzheimer's disease (AD) can cause PPA, but a quantitative investigation of the relationships between NFTs, APs and in vivo cortical atrophy in PPA-AD is lacking. The present study measured cortical atrophy from corresponding bilateral regions in five PPA-AD participants with in vivo magnetic resonance imaging scans 7-30 months before death and acquired stereologic estimates of NFTs and dense-core APs visualized with the Thioflavin-S stain. Linear mixed models accounting for repeated measures and stratified by hemisphere and region (language vs. non-language) were used to determine the relationships between cortical atrophy and AD neuropathology and their regional selectivity. Consistent with the aphasic profile of PPA, left language regions displayed more cortical atrophy (P = 0.01) and NFT densities (P = 0.02) compared to right language homologues. Left language regions also showed more cortical atrophy (P < 0.01) and NFT densities (P = 0.02) than left non-language regions. A subset of data was analyzed to determine the predilection of AD neuropathology for neocortical regions compared to entorhinal cortex in the left hemisphere, which showed that the three most atrophied language regions had greater NFT (P = 0.04) and AP densities (P < 0.01) than the entorhinal cortex. These results provide quantitative evidence that NFT accumulation in PPA selectively targets the language network and may not follow the Braak staging of neurofibrillary degeneration characteristic of amnestic AD. Only NFT densities, not AP densities, were positively associated with cortical atrophy within left language regions (P < 0.01) and right language homologues (P < 0.01). Given previous findings from amnestic AD, the current study of PPA-AD provides converging evidence that NFTs are the principal determinants of atrophy and clinical phenotypes associated with AD.

Neurofilament light chain plasma concentration predicts neurodegeneration and clinical progression in nondemented elderly adults

Previous studies demonstrated that plasma neurofilament light chain (NFL) played important predictive roles in disease progression and neurodegeneration in the preclinical phase of familial Alzheimer’s disease (AD). However, whether plasma NFL has the same predictive roles in sporadic AD is still unclear. In this study, 243 cognitively normal (CN) participants from the ADNI database were divided into two subgroups (CN- and CN+) according to CSF Aβ or AV45-PET. Associations of baseline plasma NFL concentrations or rate of change in plasma NFL with longitudinal data on other biomarkers were tested by multivariate linear mixed effects models (LMEMs). Results showed that plasma NFL concentration and its rate of change were already abnormally high in the preclinical phase of AD. Plasma NFL was associated with three core AD-related biomarkers in preclinical phase. Baseline plasma NFL, but not its rate of change, played predictive roles in both cognitive decline (β = -0.0349, p = 0.0274) and hippocampal atrophy (β = -0.0351, p = 0.0088), especially for preclinical AD participants. In summary, these results indicated that baseline plasma NFL, but not its rate of change, may be a valuable noninvasive tool to assess neurodegeneration and predict longitudinal disease progression in preclinical AD individuals.

Risk Factors Associated with Cortical Thickness and White Matter Hyperintensities in Dementia Free Okinawan Elderly

Background:

Cortical gray matter (GM) and white matter (WM) deterioration are signals of neurodegeneration and increased dementia risk; however, their specific etiologies in dementia-free aging is unclear.

Objective:

The objective of this study was to examine potentially modifiable risk factors of GM and WM degeneration in a well-characterized cohort of dementia-free elderly.

Methods:

96 Okinawan elderly participants (age 83.6) from the Keys to Optimal Cognitive Aging Project (KOCOA) underwent MRI and cognitive evaluation. Serum markers of inflammation (interleukin-6 (IL-6), high sensitivity C-reactive protein), cerebrovascular disease (systolic blood pressure (SBP) 140+, hemoglobin A1C (HgbA1C), total cholesterol), and essential minerals (copper (Cu), magnesium, and calcium) were examined in relation to mean cortical thickness (MCT) and white matter hyperintensities (WMH), adjusting for age and gender. Voxel-based morphometry (VBM) analyses identified relationships between regional GM density and the above markers.

Results:

Decreased MCT was associated with SBP 140 + (p = 0.029) and increased serum IL-6 (p = 0.036), HgbA1C (p = 0.002), and Cu (p = 0.025). In VBM analyses, increased IL-6, HgbA1C, and Cu were associated with decreased GM density in temporal lobe regions. HgbA1C (p = 0.004) was associated with greater WMH volume.

Conclusions:

Peripheral markers of Cu, CVD risk, and inflammation are associated with MRI-markers of decreased brain health in dementia-free Okinawan elderly, with regional cortical thinning in areas involved in early accumulation of Alzheimer’s disease pathology. Results identify potentially modifiable biomarkers as targets in the prevention of dementia in older individuals.

Brain MRI findings related to Alzheimer's disease in older African American adults

Although a substantial body of research has identified brain MRI measures as important markers of Alzheimer's disease (AD) risk, progression, and treatment response, most of that research has been performed in non-Hispanic white American populations, leading to questions about the utility of the brain MRI measures among individuals of other races or ethnicities. African American individuals in particular are under-represented in AD research, and may exhibit differences in prevalence of AD risk factors, prevalence of AD, incidence of AD, the clinical course of cognitive decline, and AD neuropathology, each of which could influence the utility of brain MRI markers. Unfortunately, while current evidence suggests that African Americans exhibit poorer brain health late in life based on brain MRI measurements, several other aspects of brain MRI markers in this population are unclear, including trajectories of brain MRI markers leading up to old age, relationships between traditional brain health risk factors and brain MRI findings, and the status of brain MRI markers as correlates of cognitive impairment. This unclear state of affairs highlights the urgency of future research in which large numbers of older African American adults contribute longitudinal brain MRI measurements concurrent with clinical, cognitive, and molecular biomarker measurements, ideally in the context of AD preventive or therapeutic trials.

Tau protein aggregation is associated with cellular senescence in the brain

Tau protein accumulation is the most common pathology among degenerative brain diseases, including Alzheimer's disease (AD), progressive supranuclear palsy (PSP), traumatic brain injury (TBI), and over twenty others. Tau-containing neurofibrillary tangle (NFT) accumulation is the closest correlate with cognitive decline and cell loss (Arriagada, Growdon, Hedley-Whyte, & Hyman, ), yet mechanisms mediating tau toxicity are poorly understood. NFT formation does not induce apoptosis (de Calignon, Spires-Jones, Pitstick, Carlson, & Hyman, 2009), which suggests that secondary mechanisms are driving toxicity. Transcriptomic analyses of NFT-containing neurons microdissected from postmortem AD brain revealed an expression profile consistent with cellular senescence. This complex stress response induces aberrant cell cycle activity, adaptations to maintain survival, cellular remodeling, and metabolic dysfunction. Using four AD transgenic mouse models, we found that NFTs, but not Aβ plaques, display a senescence-like phenotype. Cdkn2a transcript level, a hallmark measure of senescence, directly correlated with brain atrophy and NFT burden in mice. This relationship extended to postmortem brain tissue from humans with PSP to indicate a phenomenon common to tau toxicity. Tau transgenic mice with late-stage pathology were treated with senolytics to remove senescent cells. Despite the advanced age and disease progression, MRI brain imaging and histopathological analyses indicated a reduction in total NFT density, neuron loss, and ventricular enlargement. Collectively, these findings indicate a strong association between the presence of NFTs and cellular senescence in the brain, which contributes to neurodegeneration. Given the prevalence of tau protein deposition among neurodegenerative diseases, these findings have broad implications for understanding, and potentially treating, dozens of brain diseases.

Noninvasive optical estimation of CSF thickness for brain-atrophy monitoring

Dementia disorders are increasingly becoming sources of a broad range of problems, strongly interfering with the normal daily tasks of a growing number of individuals. Such neurodegenerative diseases are often accompanied with progressive brain atrophy that, at late stages, leads to drastically reduced brain dimensions. Currently, this structural change could be followed with X-ray computed tomography (XCT) or magnetic resonance imaging (MRI), but they share numerous disadvantages in terms of usability, invasiveness and costs. In this work, we aim to retrieve information concerning the brain-atrophy stage and its evolution, proposing a novel approach based on non-invasive time-resolved near infra-red (tr-NIR) measurements. For this purpose, we created a set of virtual human-head atlases in which we eroded the brain as it would happen in a clinical brain-atrophy progression. These realistic meshes were used to simulate a longitudinal tr-NIR study, investigating the effects of an increased amount of cerebral spinal fluid (CSF) in the photon diffusion. The analysis of late photons in the time-resolved reflectance curve-obtained via accurate Monte Carlo simulations-exhibited peculiar slope-changes upon CSF layer increase. The visibility of the effect under several measurement conditions suggested good sensitivity to CSF variation, even in the case of real measurement and under different geometrical models. The robustness of the results might promote the technique as a potential indicator of the dementia progression, relying only on fast and non-invasive optical observations.

A Systematic Review of Longitudinal Studies Which Measure Alzheimer's Disease Biomarkers

Alzheimer’s disease (AD) is a progressive and fatal neurodegenerative disease, with no effective treatment or cure. A gold standard therapy would be treatment to slow or halt disease progression; however, knowledge of causation in the early stages of AD is very limited. In order to determine effective endpoints for possible therapies, a number of quantitative surrogate markers of disease progression have been suggested, including biochemical and imaging biomarkers. The dynamics of these various surrogate markers over time, particularly in relation to disease development, are, however, not well characterized. We reviewed the literature for studies that measured cerebrospinal fluid or plasma amyloid-β and tau, or took magnetic resonance image or fluorodeoxyglucose/Pittsburgh compound B-positron electron tomography scans, in longitudinal cohort studies. We summarized the properties of the major cohort studies in various countries, commonly used diagnosis methods and study designs. We have concluded that additional studies with repeat measures over time in a representative population cohort are needed to address the gap in knowledge of AD progression. Based on our analysis, we suggest directions in which research could move in order to advance our understanding of this complex disease, including repeat biomarker measurements, standardization and increased sample sizes.

Clinical Neurology and Epidemiology of the Major Neurodegenerative Diseases

Neurodegenerative diseases are a common cause of morbidity and cognitive impairment in older adults. Most clinicians who care for the elderly are not trained to diagnose these conditions, perhaps other than typical Alzheimer's disease (AD). Each of these disorders has varied epidemiology, clinical symptomatology, laboratory and neuroimaging features, neuropathology, and management. Thus, it is important that clinicians be able to differentiate and diagnose these conditions accurately. This review summarizes and highlights clinical aspects of several of the most commonly encountered neurodegenerative diseases, including AD, frontotemporal dementia (FTD) and its variants, progressive supranuclear palsy (PSP), corticobasal degeneration (CBD), Parkinson's disease (PD), dementia with Lewy bodies (DLB), multiple system atrophy (MSA), and Huntington's disease (HD). For each condition, we provide a brief overview of the epidemiology, defining clinical symptoms and diagnostic criteria, relevant imaging and laboratory features, genetics, pathology, treatments, and differential diagnosis.

Radiological-Pathological Correlation in Alzheimer's Disease: Systematic Review of Antemortem Magnetic Resonance Imaging Findings

BACKGROUND

The standard method of ascertaining Alzheimer's disease (AD) remains postmortem assessment of amyloid plaques and neurofibrillary degeneration. Vascular pathology, Lewy bodies, TDP-43, and hippocampal sclerosis are frequent comorbidities. There is therefore a need for biomarkers that can assess these etiologies and provide a diagnosis in vivo.

OBJECTIVE

We conducted a systematic review of published radiological-pathological correlation studies to determine the relationship between antemortem magnetic resonance imaging (MRI) and neuropathological findings in AD.

METHODS

We explored PubMed in June-July 2015 using "Alzheimer's disease" and combinations of radiological and pathological terms. After exclusion following screening and full-text assessment of the 552 extracted manuscripts, three others were added from their reference list. In the end, we report results based on 27 articles.

RESULTS

Independently of normal age-related brain atrophy, AD pathology is associated with whole-brain and hippocampal atrophy and ventricular expansion as observed on T1-weighted images. Moreover, cerebral amyloid angiopathy and cortical microinfarcts are also related to brain volume loss in AD. Hippocampal sclerosis and TDP-43 are associated with hippocampal and medial temporal lobe atrophy, respectively. Brain volume loss correlates more strongly with tangles than with any other pathological finding. White matter hyperintensities observed on proton density, T2-weighted and FLAIR images are strongly related to vascular pathologies, but are also associated with other histological changes such as gliosis or demyelination.

CONCLUSION

Cerebral atrophy and white matter changes in the living brain reflect underlying neuropathology and may be detectable using antemortem MRI. In vivo MRI may therefore be an avenue for AD pathological staging.

Ventricular and Periventricular Anomalies in the Aging and Cognitively Impaired Brain

Ventriculomegaly (expansion of the brain’s fluid-filled ventricles), a condition commonly found in the aging brain, results in areas of gliosis where the ependymal cells are replaced with dense astrocytic patches. Loss of ependymal cells would compromise trans-ependymal bulk flow mechanisms required for clearance of proteins and metabolites from the brain parenchyma. However, little is known about the interplay between age-related ventricle expansion, the decline in ependymal integrity, altered periventricular fluid homeostasis, abnormal protein accumulation and cognitive impairment. In collaboration with the Baltimore Longitudinal Study of Aging (BLSA) and Alzheimer’s Disease Neuroimaging Initiative (ADNI), we analyzed longitudinal structural magnetic resonance imaging (MRI) and subject-matched fluid-attenuated inversion recovery (FLAIR) MRI and periventricular biospecimens to map spatiotemporally the progression of ventricle expansion and associated periventricular edema and loss of transependymal exchange functions in healthy aging individuals and those with varying degrees of cognitive impairment. We found that the trajectory of ventricle expansion and periventricular edema progression correlated with degree of cognitive impairment in both speed and severity, and confirmed that areas of expansion showed ventricle surface gliosis accompanied by edema and periventricular accumulation of protein aggregates, suggesting impaired clearance mechanisms in these regions. These findings reveal pathophysiological outcomes associated with normal brain aging and cognitive impairment, and indicate that a multifactorial analysis is best suited to predict and monitor cognitive decline.

Rates of hippocampal atrophy and presence of post-mortem TDP-43 in patients with Alzheimer's disease: a longitudinal retrospective study

Background

Post-mortem studies have not identified an association between beta-amyloid or tau and rates of hippocampal atrophy in Alzheimer’s disease. TAR DNA binding protein of 43kDa (TDP-43) is another protein recently linked to Alzheimer’s disease. We aimed to determine whether hippocampal TDP-43 is associated with faster rates of hippocampal atrophy.

Methods

Two-hundred ninety-eight autopsied cases with Alzheimer’s spectrum disease that had antemortem head MRI scans between 1/1/1999–12/31/2012 recruited into the Mayo Clinic Alzheimer’s Disease Research Center or Patient Registry/Study of Aging were analyzed. TDP-43 immunohistochemistry was performed and cases classified as follows: no TDP-43; TDP-43 restricted to amygdala; and TDP-43 spreading into hippocampus. Eight-hundred sixteen MRI scans, spanning 1.0–11.2 years prior to death, were analyzed. We utilized longitudinal FreeSurfer and tensor-based morphometry with symmetric normalization to calculate hippocampal volume on all serial MRI and performed linear mixed-effects regression models to estimate associations between TDP-43 and rate of hippocampal atrophy, and determine the trajectory of TDP-43 associated atrophy.

Findings

One-hundred forty-one cases showed no TDP-43, 33 had TDP-43 restricted to the amygdala and 124 had TDP-43 in hippocampus. Cases with hippocampal TDP-43 had faster rates of hippocampal atrophy compared to cases with amygdala-only TDP-43 and those without TDP-43 in cases with an intermediate-high likelihood of having Alzheimer’s disease (N=261). Hippocampal TDP-43 was not associated with rate of hippocampal atrophy in cases with low likelihood of having Alzheimer’s disease (N=37). The trajectory analysis suggested that increased rates of TDP-43 associated hippocampal atrophy may be occurring at least 10-years before death. Results were similar for FreeSurfer and tensor-based morphometry.

Interpretation

In Alzheimer’s disease, TDP-43 should be considered a potential factor related to increased rates of hippocampal atrophy. Given the importance of hippocampal atrophy in Alzheimer’s disease, it is imperative that we develop techniques for detecting TDP-43 pathology in-vivo.

Funding

National Institute of Aging

Diagnostic and Prognostic Utility of the Synaptic Marker Neurogranin in Alzheimer Disease

IMPORTANCE

Synaptic loss is an early pathologic substrate of Alzheimer disease (AD). Neurogranin is a postsynaptic neuronal protein that has demonstrated utility as a cerebrospinal fluid (CSF) marker of synaptic loss in AD.

OBJECTIVE

To investigate the diagnostic and prognostic utility of CSF neurogranin levels in a large, well-characterized cohort of individuals with symptomatic AD and cognitively normal controls.

DESIGN, SETTING, AND PARTICIPANTS

A cross-sectional and longitudinal observational study of cognitive decline in patients with symptomatic AD and cognitively normal controls was performed. Participants were individuals with a clinical diagnosis of early symptomatic AD and cognitively normal controls who were enrolled in longitudinal studies of aging and dementia at the Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine, from January 21, 2000, through March 21, 2011. Data analysis was performed from November 1, 2013, to March 31, 2015.

MAIN OUTCOMES AND MEASURES

Correlations between baseline CSF biomarker levels and future cognitive decline in patients with symptomatic AD and cognitively normal controls over time.

RESULTS

A total of 302 individuals (mean [SE] age, 73.1 [0.4] years) were included in this study (95 patients [52 women and 43 men] with AD and 207 controls [125 women and 82 men]). The CSF neurogranin levels differentiated patients with early symptomatic AD from controls with comparable diagnostic utility (mean [SE] area under the receiver operating characteristic curve, 0.71 [0.03]; 95% CI, 0.64-0.77) to the other CSF biomarkers. The CSF neurogranin levels correlated with brain atrophy (normalized whole-brain volumes: adjusted r = -0.38, P = .02; hippocampal volumes: adjusted r = -0.36, P = .03; entorhinal volumes: adjusted r = -0.46, P = .006; and parahippocampal volumes: adjusted r = -0.47, P = .005, n = 38) in AD and with amyloid load (r = 0.39, P = .02, n = 36) in preclinical AD. The CSF neurogranin levels predicted future cognitive impairment (adjusted hazard ratio, 1.89; 95% CI, 1.29-2.78; P = .001 as a continuous measure, and adjusted hazard ratio, 2.78; 95% CI, 1.13-5.99; P = .02 as a categorical measure using the 85th percentile cutoff value) in controls and rates of cognitive decline (Clinical Dementia Rating sum of boxes score: β estimate, 0.29; P = .001; global composite scores: β estimate, -0.11; P = .001; episodic memory scores: β estimate, -0.18; P < .001; and semantic memory scores: β estimate, -0.06; P = .04, n = 57) in patients with symptomatic AD over time, similarly to the CSF proteins VILIP-1, tau, and p-tau181.

CONCLUSIONS AND RELEVANCE

The CSF levels of the synaptic marker neurogranin offer diagnostic and prognostic utility for early symptomatic AD that is comparable to other CSF markers of AD. Importantly, CSF neurogranin complements the collective ability of these markers to predict future cognitive decline in cognitively normal individuals and, therefore, will be a useful addition to the current panel of AD biomarkers.

Association of In Vivo [18F]AV-1451 Tau PET Imaging Results With Cortical Atrophy and Symptoms in Typical and Atypical Alzheimer Disease

Importance

Previous postmortem studies have long demonstrated that neurofibrillary tangles made of hyperphosphorylated tau proteins are closely associated with Alzheimer disease clinical phenotype and neurodegeneration pattern. Validating these associations in vivo will lead to new diagnostic tools for Alzheimer disease and better understanding of its neurobiology.

Objective

To examine whether topographical distribution and severity of hyperphosphorylated tau pathologic findings measured by fluorine 18-labeled AV-1451 ([18F]AV-1451) positron emission tomographic (PET) imaging are linked with clinical phenotype and cortical atrophy in patients with Alzheimer disease.

Design, Setting, and Participants

This observational case series, conducted from July 1, 2012, to July 30, 2015, in an outpatient referral center for patients with neurodegenerative diseases, included 6 patients: 3 with typical amnesic Alzheimer disease and 3 with atypical variants (posterior cortical atrophy, logopenic variant primary progressive aphasia, and corticobasal syndrome). Patients underwent [18F]AV-1451 PET imaging to measure tau burden, carbon 11-labeled Pittsburgh Compound B ([11C]PiB) PET imaging to measure amyloid burden, and structural magnetic resonance imaging to measure cortical thickness. Seventy-seven age-matched controls with normal cognitive function also underwent structural magnetic resonance imaging but not tau or amyloid PET imaging.

Main Outcomes and Measures

Tau burden, amyloid burden, and cortical thickness.

Results

In all 6 patients (3 women and 3 men; mean age 61.8 years), the underlying clinical phenotype was associated with the regional distribution of the [18F]AV-1451 signal. Furthermore, within 68 cortical regions of interest measured from each patient, the magnitude of cortical atrophy was strongly correlated with the magnitude of [18F]AV-1451 binding (3 patients with amnesic Alzheimer disease, r = -0.82; P < .001; r = -0.70; P < .001; r = -0.58; P < .001; and 3 patients with nonamnesic Alzheimer disease, r = -0.51; P < .001; r = -0.63; P < .001; r = -0.70; P < .001), but not of [11C]PiB binding.

Conclusions and Relevance

These findings provide further in vivo evidence that distribution of the [18F]AV-1451 signal as seen on results of PET imaging is a valid marker of clinical symptoms and neurodegeneration. By localizing and quantifying hyperphosphorylated tau in vivo, results of tau PET imaging will likely serve as a key biomarker that links a specific type of molecular Alzheimer disease neuropathologic condition with clinically significant neurodegeneration, which will likely catalyze additional efforts to develop disease-modifying therapeutics.

Less Daily Computer Use is Related to Smaller Hippocampal Volumes in Cognitively Intact Elderly

Background: Computer use is becoming a common activity in the daily life of older individuals and declines over time in those with mild cognitive impairment (MCI). The relationship between daily computer use (DCU) and imaging markers of neurodegeneration is unknown.

Objective:The objective of this study was to examine the relationship between average DCU and volumetric markers of neurodegeneration on brain MRI.

Methods: Cognitively intact volunteers enrolled in the Intelligent Systems for Assessing Aging Change study underwent MRI. Total in-home computer use per day was calculated using mouse movement detection and averaged over a one-month period surrounding the MRI. Spearman’s rank order correlation (univariate analysis) and linear regression models (multivariate analysis) examined hippocampal, gray matter (GM), white matter hyperintensity (WMH), and ventricular cerebral spinal fluid (vCSF) volumes in relation to DCU. A voxel-based morphometry analysis identified relationships between regional GM density and DCU.

Results: Twenty-seven cognitively intact participants used their computer for 51.3 minutes per day on average. Less DCU was associated with smaller hippocampal volumes (r = 0.48, p = 0.01), but not total GM, WMH, or vCSF volumes. After adjusting for age, education, and gender, less DCU remained associated with smaller hippocampal volume (p = 0.01). Voxel-wise analysis demonstrated that less daily computer use was associated with decreased GM density in the bilateral hippocampi and temporal lobes.

Conclusions: Less daily computer use is associated with smaller brain volume in regions that are integral to memory function and known to be involved early with Alzheimer’s pathology and conversion to dementia. Continuous monitoring of daily computer use may detect signs of preclinical neurodegeneration in older individuals at risk for dementia.