Amyloid-driven disruption of default mode network connectivity in cognitively healthy individuals

Cortical accumulation of amyloid beta is one of the first events of Alzheimer's disease pathophysiology, and has been suggested to follow a consistent spatiotemporal ordering, starting in the posterior cingulate cortex, precuneus and medio-orbitofrontal cortex. These regions overlap with those of the default mode network, a brain network also involved in memory functions. Aberrant default mode network functional connectivity and higher network sparsity have been reported in prodromal and clinical Alzheimer's disease. We investigated the association between amyloid burden and default mode network connectivity in the preclinical stage of Alzheimer's disease and its association with longitudinal memory decline. We included 173 participants, in which amyloid burden was assessed both in CSF by the amyloid beta 42/40 ratio, capturing the soluble part of amyloid pathology, and in dynamic PET scans calculating the non-displaceable binding potential in early-stage regions. The default mode network was identified with resting-state functional MRI. Then, we calculated functional connectivity in the default mode network, derived from independent component analysis, and eigenvector centrality, a graph measure recursively defining important nodes on the base of their connection with other important nodes. Memory was tested at baseline, 2- and 4-year follow-up. We demonstrated that higher amyloid burden as measured by both CSF amyloid beta 42/40 ratio and non-displaceable binding potential in the posterior cingulate cortex was associated with lower functional connectivity in the default mode network. The association between amyloid burden (CSF and non-displaceable binding potential in the posterior cingulate cortex) and aberrant default mode network connectivity was confirmed at the voxel level with both functional connectivity and eigenvector centrality measures, and it was driven by voxel clusters localized in the precuneus, cingulate, angular and left middle temporal gyri. Moreover, we demonstrated that functional connectivity in the default mode network predicts longitudinal memory decline synergistically with regional amyloid burden, as measured by non-displaceable binding potential in the posterior cingulate cortex. Taken together, these results suggest that early amyloid beta deposition is associated with aberrant default mode network connectivity in cognitively healthy individuals and that default mode network connectivity markers can be used to identify subjects at risk of memory decline

Neurobiological basis and risk factors of persistent fatigue and concentration problems after COVID-19: study protocol for a prospective case–control study (VeCosCO)

Introduction: The risk factors for persistent fatigue and cognitive complaints after infection with SARS-CoV-2 and the underlying pathophysiology are largely unknown. Both clinical factors and cognitive-behavioural factors have been suggested to play a role in the perpetuation of complaints. A neurobiological aetiology, such as neuroinflammation, could be the underlying pathophysiological mechanism for persisting complaints. To unravel factors associated with persisting complaints, VeCosCO will compare individuals with and without persistent fatigue and cognitive complaints >3 months after infection with SARS-CoV-2. The study consists of two work packages. The first work package aims to (1) investigate the relation between persisting complaints and neuropsychological functioning; (2) determine risk factors and at-risk phenotypes for the development of persistent fatigue and cognitive complaints, including the presence of postexertional malaise and (3) describe consequences of persistent complaints on quality of life, healthcare consumption and physical functioning. The second work package aims to (1) determine the presence of neuroinflammation with [18F]DPA-714 whole-body positron emission tomography (PET) scans in patients with persisting complaints and (2) explore the relationship between (neuro)inflammation and brain structure and functioning measured with MRI. / Methods and analysis: This is a prospective case–control study in participants with and without persistent fatigue and cognitive complaints, >3 months after laboratory-confirmed SARS-CoV-2 infection. Participants will be mainly included from existing COVID-19 cohorts in the Netherlands covering the full spectrum of COVID-19 acute disease severity. Primary outcomes are neuropsychological functioning, postexertional malaise, neuroinflammation measured using [18F]DPA-714 PET, and brain functioning and structure using (f)MRI. / Ethics and dissemination: Work package 1 (NL79575.018.21) and 2 (NL77033.029.21) were approved by the medical ethical review board of the Amsterdam University Medical Centers (The Netherlands). Informed consent is required prior to participation in the study. Results of this study will be submitted for publication in peer-reviewed journals and shared with the key population

Assessing Amyloid Pathology in Cognitively Normal Subjects Using F-18-Flutemetamol PET: Comparing Visual Reads and Quantitative Methods

Our objective was to determine the optimal approach for assessing amyloid disease in a cognitively normal elderly population. Methods: Dynamic 18F-flutemetamol PET scans were acquired using a coffeebreak protocol (a 0- to 30-min scan and a 90- to 110-min scan) on 190 cognitively normal elderly individuals (mean age, 70.4 y; 60% female). Parametric images were generated from SUV ratio (SUVr) and nondisplaceable binding potential (BPND) methods, with cerebellar gray matter as a reference region, and were visually assessed by 3 trained readers. Interreader agreement was calculated using κ-statistics, and semiquantitative values were obtained. Global cutoffs were calculated for both SUVr and BPND using a receiver-operating-characteristic analysis and the Youden index. Visual assessment was related to semiquantitative classifications. Results: Interreader agreement in visual assessment was moderate for SUVr (κ 5 0.57) and good for BPND images (κ 5 0.77). There was discordance between readers for 35 cases (18%) using SUVr and for 15 cases (8%) using BPND, with 9 overlapping cases. For the total cohort, the mean (±SD) SUVr and BPND were 1.33 (±0.21) and 0.16 (±0.12), respectively. Most of the 35 cases (91%) for which SUVr image assessment was discordant between readers were classified as negative based on semiquantitative measurements. Conclusion: The use of parametric BPND images for visual assessment of 18F-flutemetamol in a population with low amyloid burden improves interreader agreement. Implementing semiquantification in addition to visual assessment of SUVr images can reduce false-positive classification in this population

Prevalence and prognosis of Alzheimer's disease at the mild cognitive impairment stage

Vos et al. compare the prevalence and prognosis of Alzheimer's disease at the mild cognitive impairment stage based on the IWG-1, IWG-2 and NIA-AA criteria. All three aid identification of early Alzheimer's disease, but combining amyloid and neuronal injury markers according to the NIA-AA criteria offers the most accurate prognosi

Current paradigm of the 18-kDa translocator protein (TSPO) as a molecular target for PET imaging in neuroinflammation and neurodegenerative diseases

Neuroinflammation is a process characterised by drastic changes in microglial morphology and by marked upregulation of the 18-kDa translocator protein (TSPO) on the mitochondria. The continual increase in incidence of neuroinflammation and neurodegenerative diseases poses a major health issue in many countries, requiring more innovative diagnostic and monitoring tools. TSPO expression may constitute a biomarker for brain inflammation that could be monitored by using TSPO tracers as neuroimaging agents. From medical imaging perspectives, this review focuses on the current concepts related to the TSPO, and discusses briefly on the status of its PET imaging related to neuroinflammation and neurodegenerative diseases in humans

Adopting transfer learning for neuroimaging: a comparative analysis with a custom 3D convolution neural network model.

BACKGROUND In recent years, neuroimaging with deep learning (DL) algorithms have made remarkable advances in the diagnosis of neurodegenerative disorders. However, applying DL in different medical domains is usually challenged by lack of labeled data. To address this challenge, transfer learning (TL) has been applied to use state-of-the-art convolution neural networks pre-trained on natural images. Yet, there are differences in characteristics between medical and natural images, also image classification and targeted medical diagnosis tasks. The purpose of this study is to investigate the performance of specialized and TL in the classification of neurodegenerative disorders using 3D volumes of 18F-FDG-PET brain scans. RESULTS Results show that TL models are suboptimal for classification of neurodegenerative disorders, especially when the objective is to separate more than two disorders. Additionally, specialized CNN model provides better interpretations of predicted diagnosis. CONCLUSIONS TL can indeed lead to superior performance on binary classification in timely and data efficient manner, yet for detecting more than a single disorder, TL models do not perform well. Additionally, custom 3D model performs comparably to TL models for binary classification, and interestingly perform better for diagnosis of multiple disorders. The results confirm the superiority of the custom 3D-CNN in providing better explainable model compared to TL adopted ones

Disease- and age-related changes in histone acetylation at gene promoters in psychiatric disorders

Increasing evidence suggests that epigenetic factors have critical roles in gene regulation in neuropsychiatric disorders and in aging, both of which are typically associated with a wide range of gene expression abnormalities. Here, we have used chromatin immunoprecipitation-qPCR to measure levels of acetylated histone H3 at lysines 9/14 (ac-H3K9K14), two epigenetic marks associated with transcriptionally active chromatin, at the promoter regions of eight schizophrenia-related genes in n=82 postmortem prefrontal cortical samples from normal subjects and those with schizophrenia and bipolar disorder. We find that promoter-associated ac-H3K9K14 levels are correlated with gene expression levels, as measured by real-time qPCR for several genes, including, glutamic acid decarboxylase 1 (GAD1), 5-hydroxytryptamine receptor 2C (HTR2C), translocase of outer mitochondrial membrane 70 homolog A (TOMM70A) and protein phosphatase 1E (PPM1E). Ac-H3K9K14 levels of several of the genes tested were significantly negatively associated with age in normal subjects and those with bipolar disorder, but not in subjects with schizophrenia, whereby low levels of histone acetylation were observed in early age and throughout aging. Consistent with this observation, significant hypoacetylation of H3K9K14 was detected in young subjects with schizophrenia when compared with age-matched controls. Our results demonstrate that gene expression changes associated with psychiatric disease and aging result from epigenetic mechanisms involving histone acetylation. We further find that treatment with a histone deacetylase (HDAC) inhibitor alters the expression of several candidate genes for schizophrenia in mouse brain. These findings may have therapeutic implications for the clinical use of HDAC inhibitors in psychiatric disorders

Metabolic network alterations as a supportive biomarker in dementia with Lewy bodies with preserved dopamine transmission

Purpose Metabolic network analysis of FDG-PET utilizes an index of inter-regional correlation of resting state glucose metabolism and has been proven to provide complementary information regarding the disease process in parkinsonian syndromes. The goals of this study were (i) to evaluate pattern similarities of glucose metabolism and network connectivity in dementia with Lewy bodies (DLB) subjects with subthreshold dopaminergic loss compared to advanced disease stages and to (ii) investigate metabolic network alterations of FDG-PET for discrimination of patients with early DLB from other neurodegenerative disorders (Alzheimer’s disease, Parkinson’s disease, multiple system atrophy) at individual patient level via principal component analysis (PCA). Methods FDG-PETs of subjects with probable or possible DLB (n = 22) without significant dopamine deficiency (z-score < 2 in putamen binding loss on DaT-SPECT compared to healthy controls (HC)) were scaled by global-mean, prior to volume-of-interest-based analyses of relative glucose metabolism. Single region metabolic changes and network connectivity changes were compared against HC (n = 23) and against DLB subjects with significant dopamine deficiency (n = 86). PCA was applied to test discrimination of patients with DLB from disease controls (n = 101) at individual patient level. Results Similar patterns of hypo- (parietal- and occipital cortex) and hypermetabolism (basal ganglia, limbic system, motor cortices) were observed in DLB patients with and without significant dopamine deficiency when compared to HC. Metabolic connectivity alterations correlated between DLB patients with and without significant dopamine deficiency (R2 = 0.597, p < 0.01). A PCA trained by DLB patients with dopamine deficiency and HC discriminated DLB patients without significant dopaminergic loss from other neurodegenerative parkinsonian disorders at individual patient level (area-under-the-curve (AUC): 0.912). Conclusion Disease-specific patterns of altered glucose metabolism and altered metabolic networks are present in DLB subjects without significant dopaminergic loss. Metabolic network alterations in FDG-PET can act as a supporting biomarker in the subgroup of DLB patients without significant dopaminergic loss at symptoms onset

The Effects of Handling and Anesthetic Agents on the Stress Response and Carbohydrate Metabolism in Northern Elephant Seals

Free-ranging animals often cope with fluctuating environmental conditions such as weather, food availability, predation risk, the requirements of breeding, and the influence of anthropogenic factors. Consequently, researchers are increasingly measuring stress markers, especially glucocorticoids, to understand stress, disturbance, and population health. Studying free-ranging animals, however, comes with numerous difficulties posed by environmental conditions and the particular characteristics of study species. Performing measurements under either physical restraint or chemical sedation may affect the physiological variable under investigation and lead to values that may not reflect the standard functional state of the animal. This study measured the stress response resulting from different handling conditions in northern elephant seals and any ensuing influences on carbohydrate metabolism. Endogenous glucose production (EGP) was measured using [6-3H]glucose and plasma cortisol concentration was measured from blood samples drawn during three-hour measurement intervals. These measurements were conducted in weanlings and yearlings with and without the use of chemical sedatives—under chemical sedation, physical restraint, or unrestrained. We compared these findings with measurements in adult seals sedated in the field. The method of handling had a significant influence on the stress response and carbohydrate metabolism. Physically restrained weanlings and yearlings transported to the lab had increased concentrations of circulating cortisol (F11, 46 = 25.2, p<0.01) and epinephrine (F3, 12 = 5.8, p = 0.01). Physical restraint led to increased EGP (t = 3.1, p = 0.04) and elevated plasma glucose levels (t = 8.2, p<0.01). Animals chemically sedated in the field typically did not exhibit a cortisol stress response. The combination of anesthetic agents (Telazol, ketamine, and diazepam) used in this study appeared to alleviate a cortisol stress response due to handling in the field without altering carbohydrate metabolism. Measures of hormone concentrations and metabolism made under these conditions are more likely to reflect basal values