Biomarkers for CNS injury in CSF are elevated in COVID-19 and associated with neurological symptoms and disease severity

BACKGROUND: Neurological symptoms have been frequently reported in hospitalized patients with coronavirus disease 2019 (COVID-19) and biomarkers of CNS injury are reported to be increased in plasma but not extensively studied in CSF. This study examines CSF for biomarkers of CNS injury and other pathology in relation to neurological symptoms and disease severity in patients with neurological manifestations of COVID-19. METHODS: Nineteen patients with neurological symptoms and mild to critical COVID-19 were prospectively included. Extensive analysis of CSF, including measurement of biomarkers of CNS injury (neurofilament light chain protein (NfL) glial fibrillary acidic protein (GFAp) and total tau) was performed and related to neurological features and disease severity. RESULTS: Neurological symptoms included altered mental status (42%), headache (42%), central (21%) and peripheral weakness (32%). Two patients demonstrated minor pleocytosis and four patients had increased immunoglobulin G levels in CSF. Neuronal autoantibody testing using commercial tests was negative in all patients. Increased CSF levels of NfL, GFAp and total-tau protein were seen in 63%, 37%, and 16% of patients, respectively. Increased NfL correlated with disease severity, time in intensive care and level of consciousness. NfL in CSF was higher in patients with central neurological symptoms. CONCLUSION: Although limited by small sample size, our data suggest that levels of NfL, GFAp and total tau in CSF are commonly elevated in patients with COVID-19 with neurological symptoms. This is in contrast to the standard CSF work-up where pathological findings are scarce. NfL in particular, is associated with central neurological symptoms and disease severity

Synthesis of Oligodeoxyribo‐ and Oligoribonucleotides According to the H‐Phosphonate Method

Oligonucleotides can be synthesized by condensing a protected nucleoside H‐phosphonate monoester with a second nucleoside in the presence of a coupling agent to produce a dinucleoside H‐phosphonate diester. This can then be converted to a dinucleoside phosphate or to a backbone‐modified analog such as a phosphorothioate or phosphoramidite. This unit discusses four alternative methods for synthesizing nucleoside H‐phosphonate monoesters. The methods are efficient and experimentally simple, and use readily available reagents. The unit describes the activation of the monoesters, as well as competing acylation and other potential side reactions.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/143594/1/cpnc0304.pd

Mental Health of Parents and Life Satisfaction of Children: A Within-Family Analysis of Intergenerational Transmission of Well-Being

This paper addresses the extent to which there is an intergenerational transmission of mental health and subjective well-being within families. Specifically it asks whether parents’ own mental distress influences their child’s life satisfaction, and vice versa. Whilst the evidence on daily contagion of stress and strain between members of the same family is substantial, the evidence on the transmission between parental distress and children’s well-being over a longer period of time is sparse. We tested this idea by examining the within-family transmission of mental distress from parent to child’s life satisfaction, and vice versa, using rich longitudinal data on 1,175 British youths. Results show that parental distress at year t-1 is an important determinant of child’s life satisfaction in the current year. This is true for boys and girls, although boys do not appear to be affected by maternal distress levels. The results also indicated that the child’s own life satisfaction is related with their father’s distress levels in the following year, regardless of the gender of the child. Finally, we examined whether the underlying transmission correlation is due to shared social environment, empathic reactions, or transmission via parent-child interaction

Anti-SARS-CoV2 antibody responses in serum and cerebrospinal fluid of COVID-19 patients with neurological symptoms

Antibody responses to SARS-CoV-2 in serum and CSF from 16 COVID-19 patients with neurological symptoms were assessed using two independent methods. IgG specific for the virus spike protein was found in 81% of cases in serum and in 56% in CSF. SARS-CoV-2 IgG in CSF was observed in two cases with negative serology. Levels of IgG in both serum and CSF were associated with disease severity (p<0.05). All patients with elevated markers of CNS damage in CSF also had CSF antibodies (p=0.002), and CSF antibodies had the highest predictive value for neuronal damage markers of all tested clinical variables

Investigating dietary life histories and mobility of children buried in St Gertrude Church Cemetery, Riga, Latvia (15th– 17th centuries AD)

Carbon and nitrogen isotope profiles were obtained from incremental dentine analysis of 19 non‐adults from a cemetery in Riga, Latvia. The research compared the life histories and diet between people buried in two mass graves and the general cemetery. The δ13C profiles of several children from the mass graves were similar but did not resemble the patterns seen in children from the general cemetery, suggesting that they probably represented a different population group. The rise in δ15N values towards the end of the life of four individuals from one mass grave suggests they were victims of an historically documented famine

Automatic ROI Selection in Structural Brain MRI Using SOM 3D Projection

This paper presents a method for selecting Regions of Interest (ROI) in brain Magnetic Resonance Imaging (MRI) for diagnostic purposes, using statistical learning and vector quantization techniques. The proposed method models the distribution of GM and WM tissues grouping the voxels belonging to each tissue in ROIs associated to a specific neurological disorder. Tissue distribution of normal and abnormal images is modelled by a Self-Organizing map (SOM), generating a set of representative prototypes, and the receptive field (RF) of each SOM prototype defines a ROI. Moreover, the proposed method computes the relative importance of each ROI by means of its discriminative power. The devised method has been assessed using 818 images from the Alzheimer's disease Neuroimaging Initiative (ADNI) which were previously segmented through Statistical Parametric Mapping (SPM). The proposed algorithm was used over these images to parcel ROIs associated to the Alzheimer's Disease (AD). Additionally, this method can be used to extract a reduced set of discriminative features for classification, since it compresses discriminative information contained in the brain. Voxels marked by ROIs which were computed using the proposed method, yield classification results up to 90% of accuracy for controls (CN) and Alzheimer's disease (AD) patients, and 84% of accuracy for Mild Cognitive Impairment (MCI) and AD patients.This work was partly supported by the MICINN under the TEC2012-34306 project and the Consejería de Innovación, Ciencia y Empresa (Junta de Andalucía, Spain) under the Excellence Projects P09-TIC-4530 and P11-TIC-7103. Data collection and sharing for this project was funded by the Alzheimer's Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant U01 AG024904) and DOD ADNI (Department of Defense award number W81XWH-12-2-0012). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: Alzheimer's Association; Alzheimer's Drug Discovery Foundation; BioClinica, Inc.; Biogen Idec Inc.; Bristol-Myers Squibb Company; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc.; GE Healthcare; Innogenetics, N.V.; IXICO Ltd.; Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical Research & Development LLC.; Medpace, Inc.; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; NeuroRxResearch; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Synarc Inc.; and Takeda Pharmaceutical Company. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health (www.fnih.org). The grantee organization is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer's Disease Cooperative Study at the University of California, San Diego. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California

Interpretation of Brain Morphology in Association to Alzheimer's Disease Dementia Classification Using Graph Convolutional Networks on Triangulated Meshes

We propose a mesh-based technique to aid in the classification of Alzheimer's disease dementia (ADD) using mesh representations of the cortex and subcortical structures. Deep learning methods for classification tasks that utilize structural neuroimaging often require extensive learning parameters to optimize. Frequently, these approaches for automated medical diagnosis also lack visual interpretability for areas in the brain involved in making a diagnosis. This work: (a) analyzes brain shape using surface information of the cortex and subcortical structures, (b) proposes a residual learning framework for state-of-the-art graph convolutional networks which offer a significant reduction in learnable parameters, and (c) offers visual interpretability of the network via class-specific gradient information that localizes important regions of interest in our inputs. With our proposed method leveraging the use of cortical and subcortical surface information, we outperform other machine learning methods with a 96.35% testing accuracy for the ADD vs. healthy control problem. We confirm the validity of our model by observing its performance in a 25-trial Monte Carlo cross-validation. The generated visualization maps in our study show correspondences with current knowledge regarding the structural localization of pathological changes in the brain associated to dementia of the Alzheimer's type.Comment: Accepted for the Shape in Medical Imaging (ShapeMI) workshop at MICCAI International Conference 202

Plasma based markers of [11C] PiB-PET brain amyloid burden.

PublishedJournal ArticleResearch Support, N.I.H., ExtramuralResearch Support, Non-U.S. Gov'tChanges in brain amyloid burden have been shown to relate to Alzheimer's disease pathology, and are believed to precede the development of cognitive decline. There is thus a need for inexpensive and non-invasive screening methods that are able to accurately estimate brain amyloid burden as a marker of Alzheimer's disease. One potential method would involve using demographic information and measurements on plasma samples to establish biomarkers of brain amyloid burden; in this study data from the Alzheimer's Disease Neuroimaging Initiative was used to explore this possibility. Sixteen of the analytes on the Rules Based Medicine Human Discovery Multi-Analyte Profile 1.0 panel were found to associate with [(11)C]-PiB PET measurements. Some of these markers of brain amyloid burden were also found to associate with other AD related phenotypes. Thirteen of these markers of brain amyloid burden--c-peptide, fibrinogen, alpha-1-antitrypsin, pancreatic polypeptide, complement C3, vitronectin, cortisol, AXL receptor kinase, interleukin-3, interleukin-13, matrix metalloproteinase-9 total, apolipoprotein E and immunoglobulin E--were used along with co-variates in multiple linear regression, and were shown by cross-validation to explain >30% of the variance of brain amyloid burden. When a threshold was used to classify subjects as PiB positive, the regression model was found to predict actual PiB positive individuals with a sensitivity of 0.918 and a specificity of 0.545. The number of APOE [Symbol: see text] 4 alleles and plasma apolipoprotein E level were found to contribute most to this model, and the relationship between these variables and brain amyloid burden was explored.Alzheimer's Disease Neuroimaging Initiative (ADNI)Canadian Institutes of Health ResearchFoundation for the National Institutes of HealthNational Institutes of HealthInnoMed, European Union of the Sixth Framework programNational Institutes for Health Research Biomedical Research Centre for Mental Health at the South London and Maudsley National Health Service Foundation TrustInstitute of Psychiatry, King's College Londo

How Do I-Deals Influence Client Satisfaction? The Role of Exhaustion, Collective Commitment, and Age Diversity

This paper introduces a multi-level perspective on the relationships of idiosyncratic deals (i-deals) with organizational outcomes (i.e., client satisfaction) and investigates how and under which conditions these relationships manifest. Based on contagion theory, we proposed that the positive effects of i-deals will spill over within organizational units (indicated by reduced emotional exhaustion and enhanced collective commitment), which leads to increased customer satisfaction. Moreover, it was postulated that the effects of i-deals would be more prominent in units with high age diversity, as i-deals are more important in units where people's work-related needs are more heterogeneous due to the higher diversity in employee age. A study among 19,780 employees and 17,500 clients of a German public service organization showed support for the contagion model and showed that i-deals were negatively related to individual emotional exhaustion and subsequently positively to collective commitment within units and client satisfaction measured six months later. Emotional exhaustion and collective commitment mediated the relationships between i-deals and client satisfaction. Finally, we found that the relationships between i-deals and emotional exhaustion and client satisfaction were more strongly negative in units with high age diversity rather than in units with low age diversity, indicating the benefits of i-deals within units with high age diversity to reduce emotional exhaustion and enhance client satisfaction

Plasma proteins predict conversion to dementia from prodromal disease.

PublishedJournal ArticleMulticenter StudyResearch Support, Non-U.S. Gov'tBACKGROUND: The study aimed to validate previously discovered plasma biomarkers associated with AD, using a design based on imaging measures as surrogate for disease severity and assess their prognostic value in predicting conversion to dementia. METHODS: Three multicenter cohorts of cognitively healthy elderly, mild cognitive impairment (MCI), and AD participants with standardized clinical assessments and structural neuroimaging measures were used. Twenty-six candidate proteins were quantified in 1148 subjects using multiplex (xMAP) assays. RESULTS: Sixteen proteins correlated with disease severity and cognitive decline. Strongest associations were in the MCI group with a panel of 10 proteins predicting progression to AD (accuracy 87%, sensitivity 85%, and specificity 88%). CONCLUSIONS: We have identified 10 plasma proteins strongly associated with disease severity and disease progression. Such markers may be useful for patient selection for clinical trials and assessment of patients with predisease subjective memory complaints.Medical Research Council (MRC)Alzheimer’s Research UKThe National Institute for Health Research (NIHR) Biomedical Research CentreBiomedical Research Unit for DementiaAddNeuroMed through the EU FP6 programInnovative Medicines Initiative Joint Undertaking under an EMIF grantEuropean Union’s Seventh Framework Programme (FP7/2007-2013