Abhirup Sarkar

Sevoflurane and Isoflurane induce structural changes in brain vascular endothelial cells and increase blood−brain barrier permeability: Possible link to postoperative delirium and cognitive decline

A large percentage of patients subjected to general anesthesia at 65 years and older exhibit postoperative delirium (POD). Here, we test the hypothesis that inhaled anesthetics (IAs), such as Sevoflurane and Isoflurane, act directly on brain vascular endothelial cells (BVECs) to increase blood-brain barrier (BBB) permeability, thereby contributing to POD. Rats of young (3-5 months), middle (10-12 months) and old (17-19 months) ages were anesthetized with Sevoflurane or Isoflurane for 3h. After exposure, some were euthanized immediately; others were allowed to recover for 24h before sacrifice. Immunohistochemistry was employed to monitor the extent of BBB breach, and scanning electron microscopy (SEM) was used to examine changes in the luminal surfaces of BVECs. Quantitative immunohistochemistry revealed increased BBB permeability in older animals treated with Sevoflurane, but not Isoflurane. Extravasated immunoglobulin G showed selective affinity for pyramidal neurons. SEM demonstrated marked flattening of the luminal surfaces of BVECs in anesthetic-treated rats. Results suggest an aging-linked BBB compromise resulting from exposure to Sevoflurane. Changes in the luminal surface topology of BVECs indicate a direct effect on the plasma membrane, which may weaken or disrupt their BBB-associated tight junctions. Disruption of brain homeostasis due to plasma influx into the brain parenchyma and binding of plasma components (e.g., immunoglobulins) to neurons may contribute to POD. We propose that, in the elderly, exposure to some IAs can cause BBB compromise that disrupts brain homeostasis, perturbs neuronal function and thereby contributes to POD. If unresolved, this may progress to postoperative cognitive decline and later dementia.

Potential utility of autoantibodies as blood-based biomarkers for early detection and diagnosis of Parkinson's disease.

INTRODUCTION There is a great need to identify readily accessible, blood-based biomarkers for Parkinsons disease (PD) that are useful for accurate early detection and diagnosis. This advancement would allow early patient treatment and enrollment into clinical trials, both of which would greatly facilitate the development of new therapies for PD. METHODS Sera from a total of 398 subjects, including 103 early-stage PD subjects derived from the Deprenyl and Tocopherol Antioxidative Therapy of Parkinsonism (DATATOP) study, were screened with human protein microarrays containing 9,486 potential antigen targets to identify autoantibodies potentially useful as biomarkers for PD. A panel of selected autoantibodies with a higher prevalence in early-stage PD was identified and tested using Random Forest for its ability to distinguish early-stage PD subjects from controls and from individuals with other neurodegenerative and non-neurodegenerative diseases. RESULTS Results demonstrate that a panel of selected, blood-borne autoantibody biomarkers can distinguish early-stage PD subjects (90% confidence in diagnosis) from age- and sex-matched controls with an overall accuracy of 87.9%, a sensitivity of 94.1% and specificity of 85.5%. These biomarkers were also capable of differentiating patients with early-stage PD from those with more advanced (mild-moderate) PD with an overall accuracy of 97.5%, and could distinguish subjects with early-stage PD from those with other neurological (e.g., Alzheimers disease and multiple sclerosis) and non-neurological (e.g., breast cancer) diseases. CONCLUSION These results demonstrate, for the first time, that a panel of selected autoantibodies may prove to be useful as effective blood-based biomarkers for the diagnosis of early-stage PD.

Detection of Alzheimer's disease at mild cognitive impairment and disease progression using autoantibodies as blood-based biomarkers

There is an urgent need to identify biomarkers that can accurately detect and diagnose Alzheimers disease (AD). Autoantibodies are abundant and ubiquitous in human sera and have been previously demonstrated as disease‐specific biomarkers capable of accurately diagnosing mild‐moderate stages of AD and Parkinsons disease.

Breakdown of the Cerebrovasculature and Blood-Brain Barrier: A Mechanistic Link Between Diabetes Mellitus and Alzheimer's Disease.

Alzheimers disease (AD) and diabetes mellitus (DM) are among the most pervasive and devastating disorders that afflict people throughout the world. Although typically associated with older demographics, recent epidemiologic studies have reported parallel trends in decreasing age of onset and increasing incidence of these conditions. Promising research continues to implicate the cerebrovasculature and blood-brain barrier (BBB) as playing key roles in AD pathoetiology. Similarly, complications accompanying DM, such as diabetic nephropathy/retinopathy, cardiovascular disease, and stroke, have been rooted in vascular compromise. Not surprisingly, DM is now considered a major risk factor for AD. The purpose of this review is to highlight investigations into the role of the cerebrovasculature in the development and progression of AD. We give particular attention to studies on humans and a variety of animal model systems that have demonstrated a link between BBB dysfunction and pathological changes in the brain consistent with aging and AD. Together, these studies suggest that the vascular complications associated with chronic, poorly managed DM can lead to subclinical BBB breakdown that precedes and drives the pathological changes progressing to symptomatic AD, providing a common mechanistic thread connecting these two disorders. Furthermore, this emphasizes the need to focus on the vasculature as a potential therapeutic target with the intent of limiting BBB breakdown involved in disease initiation and progression. In conclusion, AD may be more than just an associated comorbidity of DM, and instead another manifestation of the underlying vascular pathology that is common to both.

Autoantibodies as diagnostic biomarkers for the detection and subtyping of multiple sclerosis

The goal of this preliminary proof-of-concept study was to use human protein microarrays to identify blood-based autoantibody biomarkers capable of diagnosing multiple sclerosis (MS). Using sera from 112 subjects, including 51 MS subjects, autoantibody biomarkers effectively differentiated MS subjects from age- and gender-matched normal and breast cancer controls with 95.0% and 100% overall accuracy, but not from subjects with Parkinsons disease. Autoantibody biomarkers were also useful in distinguishing subjects with the relapsing-remitting form of MS from those with the secondary progressive subtype. These results demonstrate that autoantibodies can be used as noninvasive blood-based biomarkers for the detection and subtyping of MS.

UTILITY OF AUTOANTIBODY BIOMARKERS FOR DETECTION OF ALZHEIMER'S DISEASE

misfolded proteins. Currently there is no consensus for blood based tests for these diseases. Expression profiling of small non-coding RNA’s, microRNA (miRNA), has revealed diagnostic potential in human disease such as cancer. miRNA’s can be found in the blood stream and other body fluids encapsulated in small extracellular vesicles known as exosomes.Methods: Using deep sequencing we have analysed the RNA content of exosomes from a cohort of healthy aged and Alzheimer’s patients (n1⁄449) using samples from the Australian Imaging, Biomarkers and Lifestyle Flagship Study (AIBL). miRNA associating with disease were validated using qPCR(N1⁄460), with predictions performed using RandomForest. Additional risk factors collected during the 4.5 year AIBL study were included, which consisted of baseline and 54 month clinical, medical and cognitive assessment including Amyloid-PET imaging. Results:We developed a workflow for the analysis of exosomal miRNA from human blood serum that has diagnostic potential for AD. We have identified an AD specific, 16 miRNA signature, derived from the deep sequencing data and validated in an additional set of samples. Adding established risk factors including age, sex, and APOE allele status to the panel of deregulated miRNA resulted in a sensitivity and specificity of 87% and 77% respectively for predicting AD. Furthermore, Amyloid-PET information for those HC participants incorrectly classified with AD suggested progression towards AD. Conclusions: These data suggest that an exosomal miRNA signature may be a suitable peripheral screening tool for AD and other neurodegenerative disorders such as Prion and Parkinson’s diseases.

S12. THE ‘AUTOANTIBODYOME’ IN PSYCHOSIS: A PILOT STUDY AND BLUEPRINT FOR BIOMARKER DISCOVERY

Abstract Background Recent studies seeking to describe the prevalence and significance of autoantibodies in psychotic disorders can be characterized as ‘top-down’ in theoretical approach; that is, autoantibodies to specific (usually CNS) antigens are sought based on a) the known function of the antigen (e.g. NMDAR) and its putative role in psychosis or b) the clinical observation that these autoantibodies can cause psychosis as part of a more complex neuropsychiatric presentation (e.g. autoimmune encephalitis). No candidate autoantibodies with a clear diagnostic or prognostic role have been definitively established. We sought to take an alternative, ‘bottom-up’ approach to the significance of autoantibodies in psychosis that remains agnostic as to the potential significance of any one antigen. Every individual harbours autoantibodies directed against many thousands of self-antigens and the vast majority are not disease-causing. Indeed production of autoantibodies may represent a physiological, antigen-specific ‘debris-clearing’ response to tissue destruction or damage. It follows that the autoantibody profile of any individual reflects any pathological process that is ongoing in that individual and can thus serve as a ‘readout’ of the disease state in question. Methods Sera from 20 patients with a first episode of psychosis (FEP) (males: n=16; mean age: 29.35 s.d.: 7.07) from the Genetics and Psychosis (GAP) study and 20 matched controls were analysed, using Invitrogen’s ProtoArray v5.1 Human Protein Microarrays, for the presence of IgG to 9486 unique human protein antigens which had been expressed as GST fusion proteins in insect cells, purified and spotted onto slides. Following application of a fluorescent secondary IgG, reactivity patterns were automatically read using a fluorescence scanner. Samples were split into testing and training sets, and the top 50 most differentially expressed and differentially depleted antibodies were then chosen as biomarkers. Results The top 50 expressed biomarkers from the training set correctly identified 100% of psychosis subjects from the testing set, and 80% of healthy controls (OOB estimate of error rate 10%). When training and testing sets were swapped, biomarker overlap was 46% and 90% of psychosis subjects and 90% of controls were correctly identified (OOB estimate of error rate 10%). The top 50 depleted biomarkers from the training set correctly identified 90% of psychosis subjects from the testing set, and 90% of healthy controls (OOB estimate of error rate 10%). When training and testing sets were swapped, depletion biomarker overlap was 2% and 70% of psychosis subjects and 40% of controls were correctly identified (OOB estimate of error rate 45%). Discussion The autoantibodyome in FEP differs from that of healthy individuals. In this novel pilot study, a panel of 50 differentially expressed autoantibodies allowed confident discrimination between patients and controls, potentially paving the way for development of antibody-based diagnostics for psychosis using a simple blood test and fewer autoantibodies. Depletion biomarkers, thought to represent antibodies selectively depleted from the blood due to target binding in tissues, had less replicability and utility than expression biomarkers, which may offer insights into the active role of the adaptive immune system in psychosis. Further work will attempt to validate this approach in larger samples, using psychiatric disease controls. This autoantibodyomic approach may also show promise for the identification of predictive and prognostic biomarkers in psychotic disorders.