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Article

Applicability of digital analysis and imaging technology in neuropathology assessment

by William D. Dunn; Marla Gearing; Yuna Park; Lifan Zhang; John Hanfelt; Jonathan Glass; David Gutman

2016

Subjects
  • Biology, Neuroscience
  • Biology, Bioinformatics
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Abstract:Close

Alzheimer's disease (AD) is a progressive neurological disorder that affects more than 30 million people worldwide. While various dementia-related losses in cognitive functioning are its hallmark clinical symptoms, ultimate diagnosis is based on manual neuropathological assessments using various schemas, including Braak staging, CERAD (Consortium to Establish a Registry for Alzheimer's Disease) and Thal phase scoring. Since these scoring systems are based on subjective assessment, there is inevitably some degree of variation between readers, which could affect ultimate neuropathology diagnosis. Here, we report a pilot study investigating the applicability of computer-driven image analysis for characterizing neuropathological features, as well as its potential to supplement or even replace manually derived ratings commonly performed in medical settings. In this work, we quantitatively measured amyloid beta (Aβ) plaque in various brain regions from 34 patients using a robust digital quantification algorithm. We next verified these digitally derived measures to the manually derived pathology ratings using correlation and ordinal logistic regression methods, while also investigating the association with other AD-related neuropathology scoring schema commonly used at autopsy, such as Braak and CERAD. In addition to successfully verifying our digital measurements of Aβ plaques with respective categorical measurements, we found significant correlations with most AD-related scoring schemas. Our results demonstrate the potential for digital analysis to be adapted to more complex staining procedures commonly used in neuropathological diagnosis. As the efficiency of scanning and digital analysis of histology images increases, we believe that the basis of our semi-automatic approach may better standardize quantification of neuropathological changes and AD diagnosis, ultimately leading to a more comprehensive understanding of neurological disorders and more efficient patient care.

Article

Autoantibodies as biomarkers for the prediction of neuropsychiatric events in systemic lupus erythematosus

by J G Hanly; M B Urowitz; L Su; S-C Bae; C Gordon; A Clarke; S Bernatsky; A Vasudevan; D Isenberg; A Rahman; D J Wallace; P R Fortin; D Gladman; J Romero-Diaz; J Sanchez-Guerrero; M A Dooley; I Bruce; K Steinsson; M Khamashta; S Manzi; R Ramsey-Goldman; G Sturfelt; O Nived; R van Vollenhoven; M Ramos-Casals; C Aranow; M Mackay; K Kalunian; G S Alarcón; B J Fessler; G Ruiz-Irastorza; M Petri; Sung Lim; D Kamen; C Peschken; V Farewell; K Thompson; C Theriault; J T Merrill

2011

Subjects
  • Health Sciences, General
  • Health Sciences, Epidemiology
  • Health Sciences, Medicine and Surgery
  • File Download
  • View Abstract

Abstract:Close

Objective: Neuropsychiatric events occur unpredictably in systemic lupus erythematosus (SLE) and most biomarker associations remain to be prospectively validated. This study examined a disease inception cohort of 1047 SLE patients to determine which autoantibodies at enrolment predicted subsequent neuropsychiatric events. Methods: Patients with a recent SLE diagnosis were assessed prospectively for up to 10 years for neuropsychiatric events using the American College of Rheumatology case definitions. Decision rules of graded stringency determined whether neuropsychiatric events were attributable to SLE. Associations between the first neuropsychiatric event and baseline autoantibodies (lupus anticoagulant (LA), anticardiolipin, anti- β2 glycoprotein-I, anti-ribosomal P and anti-NR2 glutamate receptor) were tested by Cox proportional hazards regression. Results: Disease duration at enrolment was 5.4±4.2 months, follow-up was 3.6±2.6 years. Patients were 89.1% female with mean (±SD) age 35.2±13.7 years. 495/1047 (47.3%) developed one or more neuropsychiatric event (total 917 events). Neuropsychiatric events attributed to SLE were 15.4% (model A) and 28.2% (model B). At enrolment 21.9% of patients had LA, 13.4% anticardiolipin, 15.1% anti-β2 glycoprotein-I, 9.2% anti-ribosomal P and 13.7% anti-NR2 antibodies. LA at baseline was associated with subsequent intracranial thrombosis (total n=22) attributed to SLE (model B) (HR 2.54, 95% CI 1.08 to 5.94). Anti-ribosomal P antibody was associated with subsequent psychosis (total n=14) attributed to SLE (model B) (HR 3.92, 95% CI 1.23 to 12.5, p=0.02). Other autoantibodies did not predict neuropsychiatric events. Conclusion: In a prospective study of 1047 recently diagnosed SLE patients, LA and anti-ribosomal P antibodies are associated with an increased future risk of intracranial thrombosis and lupus psychosis, respectively.
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