Anahita Adeli

Bio: Anahita Adeli is an academic researcher from Ohio State University. The author has contributed to research in topics: Dementia & Medicine. The author has an hindex of 16, co-authored 22 publications receiving 2149 citations. Previous affiliations of Anahita Adeli include University of Pittsburgh & Mayo Clinic.

Early role of vascular dysregulation on late-onset Alzheimer’s disease based on multifactorial data-driven analysis

Abstract: Multifactorial mechanisms underlying late-onset Alzheimer's disease (LOAD) are poorly characterized from an integrative perspective. Here spatiotemporal alterations in brain amyloid-β deposition, metabolism, vascular, functional activity at rest, structural properties, cognitive integrity and peripheral proteins levels are characterized in relation to LOAD progression. We analyse over 7,700 brain images and tens of plasma and cerebrospinal fluid biomarkers from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Through a multifactorial data-driven analysis, we obtain dynamic LOAD-abnormality indices for all biomarkers, and a tentative temporal ordering of disease progression. Imaging results suggest that intra-brain vascular dysregulation is an early pathological event during disease development. Cognitive decline is noticeable from initial LOAD stages, suggesting early memory deficit associated with the primary disease factors. High abnormality levels are also observed for specific proteins associated with the vascular system's integrity. Although still subjected to the sensitivity of the algorithms and biomarkers employed, our results might contribute to the development of preventive therapeutic interventions.

Characterization of frontotemporal dementia and/or amyotrophic lateral sclerosis associated with the GGGGCC repeat expansion in C9ORF72

Abstract: Numerous kindreds with familial frontotemporal dementia and/or amyotrophic lateral sclerosis have been linked to chromosome 9, and an expansion of the GGGGCC hexanucleotide repeat in the non-coding region of chromosome 9 open reading frame 72 has recently been identified as the pathogenic mechanism. We describe the key characteristics in the probands and their affected relatives who have been evaluated at Mayo Clinic Rochester or Mayo Clinic Florida in whom the hexanucleotide repeat expansion were found. Forty-three probands and 10 of their affected relatives with DNA available (total 53 subjects) were shown to carry the hexanucleotide repeat expansion. Thirty-six (84%) of the 43 probands had a familial disorder, whereas seven (16%) appeared to be sporadic. Among examined subjects from the 43 families (n = 63), the age of onset ranged from 33 to 72 years (median 52 years) and survival ranged from 1 to 17 years, with the age of onset 60 in 19 (30%). Clinical diagnoses among examined subjects included behavioural variant frontotemporal dementia with or without parkinsonism (n = 30), amyotrophic lateral sclerosis (n = 18), frontotemporal dementia/amyotrophic lateral sclerosis with or without parkinsonism (n = 12), and other various syndromes (n = 3). Parkinsonism was present in 35% of examined subjects, all of whom had behavioural variant frontotemporal dementia or frontotemporal dementia/amyotrophic lateral sclerosis as the dominant clinical phenotype. No subject with a diagnosis of primary progressive aphasia was identified with this mutation. Incomplete penetrance was suggested in two kindreds, and the youngest generation had significantly earlier age of onset (>10 years) compared with the next oldest generation in 11 kindreds. Neuropsychological testing showed a profile of slowed processing speed, complex attention/executive dysfunction, and impairment in rapid word retrieval. Neuroimaging studies showed bilateral frontal abnormalities most consistently, with more variable degrees of parietal with or without temporal changes; no case had strikingly focal or asymmetric findings. Neuropathological examination of 14 patients revealed a range of transactive response DNA binding protein molecular weight 43 pathology (10 type A and four type B), as well as ubiquitin-positive cerebellar granular neuron inclusions in all but one case. Motor neuron degeneration was detected in nine patients, including five patients without ante-mortem signs of motor neuron disease. While variability exists, most cases with this mutation have a characteristic spectrum of demographic, clinical, neuropsychological, neuroimaging and especially neuropathological findings.

New diagnostic EEG markers of the Alzheimer's disease using visibility graph

Abstract: A new chaos-wavelet approach is presented for electroencephalogram (EEG)-based diagnosis of Alzheimer's disease (AD) employing a recently developed concept in graph theory, visibility graph (VG). The approach is based on the research ideology that nonlinear features may not reveal differences between AD and control group in the band-limited EEG, but may represent noticeable differences in certain sub-bands. Hence, complexity of EEGs is computed using the VGs of EEGs and EEG sub-bands produced by wavelet decomposition. Two methods are employed for computation of complexity of the VGs: one based on the power of scale-freeness of a graph structure and the other based on the maximum eigenvalue of the adjacency matrix of a graph. Analysis of variation is used for feature selection. Two classifiers are applied to the selected features to distinguish AD and control EEGs: a Radial Basis Function Neural Network (RBFNN) and a two-stage classifier consisting of Principal Component Analysis (PCA) and the RBFNN. After comprehensive statistical studies, effective classification features and mathematical markers were discovered. Finally, using the discovered features and a two-stage classifier (PCA-RBFNN), a high diagnostic accuracy of 97.7% was obtained.

Basal forebrain degeneration precedes and predicts the cortical spread of Alzheimer's pathology.

Abstract: There is considerable debate whether Alzheimer's disease (AD) originates in basal forebrain or entorhinal cortex. Here we examined whether longitudinal decreases in basal forebrain and entorhinal cortex grey matter volume were interdependent and sequential. In a large cohort of age-matched older adults ranging from cognitively normal to AD, we demonstrate that basal forebrain volume predicts longitudinal entorhinal degeneration. Models of parallel degeneration or entorhinal origin received negligible support. We then integrated volumetric measures with an amyloid biomarker sensitive to pre-symptomatic AD pathology. Comparison between cognitively matched normal adult subgroups, delineated according to the amyloid biomarker, revealed abnormal degeneration in basal forebrain, but not entorhinal cortex. Abnormal degeneration in both basal forebrain and entorhinal cortex was only observed among prodromal (mildly amnestic) individuals. We provide evidence that basal forebrain pathology precedes and predicts both entorhinal pathology and memory impairment, challenging the widely held belief that AD has a cortical origin.

Blood–brain barrier breakdown in Alzheimer disease and other neurodegenerative disorders

Abstract: The blood-brain barrier (BBB) is a continuous endothelial membrane within brain microvessels that has sealed cell-to-cell contacts and is sheathed by mural vascular cells and perivascular astrocyte end-feet The BBB protects neurons from factors present in the systemic circulation and maintains the highly regulated CNS internal milieu, which is required for proper synaptic and neuronal functioning BBB disruption allows influx into the brain of neurotoxic blood-derived debris, cells and microbial pathogens and is associated with inflammatory and immune responses, which can initiate multiple pathways of neurodegeneration This Review discusses neuroimaging studies in the living human brain and post-mortem tissue as well as biomarker studies demonstrating BBB breakdown in Alzheimer disease, Parkinson disease, Huntington disease, amyotrophic lateral sclerosis, multiple sclerosis, HIV-1-associated dementia and chronic traumatic encephalopathy The pathogenic mechanisms by which BBB breakdown leads to neuronal injury, synaptic dysfunction, loss of neuronal connectivity and neurodegeneration are described The importance of a healthy BBB for therapeutic drug delivery and the adverse effects of disease-initiated, pathological BBB breakdown in relation to brain delivery of neuropharmaceuticals are briefly discussed Finally, future directions, gaps in the field and opportunities to control the course of neurological diseases by targeting the BBB are presented

Blood-Brain Barrier: From Physiology to Disease and Back

Abstract: The blood-brain barrier (BBB) prevents neurotoxic plasma components, blood cells, and pathogens from entering the brain. At the same time, the BBB regulates transport of molecules into and out of t...

Autonomous Structural Visual Inspection Using Region-Based Deep Learning for Detecting Multiple Damage Types

Abstract: Computer vision-based techniques were developed to overcome the limitations of visual inspection by trained human resources and to detect structural damage in images remotely, but most methods detect only specific types of damage, such as concrete or steel cracks. To provide quasi real-time simultaneous detection of multiple types of damages, a Faster Region-based Convolutional Neural Network (Faster R-CNN)-based structural visual inspection method is proposed. To realize this, a database including 2,366 images (with 500 × 375 pixels) labeled for five types of damages—concrete crack, steel corrosion with two levels (medium and high), bolt corrosion, and steel delamination—is developed. Then, the architecture of the Faster R-CNN is modified, trained, validated, and tested using this database. Results show 90.6%, 83.4%, 82.1%, 98.1%, and 84.7% average precision (AP) ratings for the five damage types, respectively, with a mean AP of 87.8%. The robustness of the trained Faster R-CNN is evaluated and demonstrated using 11 new 6,000 × 4,000-pixel images taken of different structures. Its performance is also compared to that of the traditional CNN-based method. Considering that the proposed method provides a remarkably fast test speed (0.03 seconds per image with 500 × 375 resolution), a framework for quasi real-time damage detection on video using the trained networks is developed.

Blood-brain barrier breakdown is an early biomarker of human cognitive dysfunction.

Abstract: Vascular contributions to cognitive impairment are increasingly recognized1-5 as shown by neuropathological6,7, neuroimaging4,8-11, and cerebrospinal fluid biomarker4,12 studies. Moreover, small vessel disease of the brain has been estimated to contribute to approximately 50% of all dementias worldwide, including those caused by Alzheimer's disease (AD)3,4,13. Vascular changes in AD have been typically attributed to the vasoactive and/or vasculotoxic effects of amyloid-β (Aβ)3,11,14, and more recently tau15. Animal studies suggest that Aβ and tau lead to blood vessel abnormalities and blood-brain barrier (BBB) breakdown14-16. Although neurovascular dysfunction3,11 and BBB breakdown develop early in AD1,4,5,8-10,12,13, how they relate to changes in the AD classical biomarkers Aβ and tau, which also develop before dementia17, remains unknown. To address this question, we studied brain capillary damage using a novel cerebrospinal fluid biomarker of BBB-associated capillary mural cell pericyte, soluble platelet-derived growth factor receptor-β8,18, and regional BBB permeability using dynamic contrast-enhanced magnetic resonance imaging8-10. Our data show that individuals with early cognitive dysfunction develop brain capillary damage and BBB breakdown in the hippocampus irrespective of Alzheimer's Aβ and/or tau biomarker changes, suggesting that BBB breakdown is an early biomarker of human cognitive dysfunction independent of Aβ and tau.