Immunosignature Differentiation of Non-Infectious Meningoencephalomyelitis and Intracranial Neoplasia in Dogs.

Bathilda B Lake,Julie Cecere,Kurt L Zimmerman,Phillip Stafford,John Henry Rossmeisl

doi:10.3389/fvets.2018.00097

Abstract

A variety of inflammatory conditions of unknown cause (meningoencephalomyelitis of unknown etiology—MUE) and neoplastic diseases can affect the central nervous system (CNS) of dogs. MUE can mimic intracranial neoplasia both clinically, radiologically and even in some cases, histologically. Serum immunosignature protein microarray assays have been used in humans to identify CNS diseases such as Alzheimer’s and neoplasia, and in dogs, to detect lymphoma and its progression. This study evaluated the effectiveness of immunosignature profiles for distinguishing between three cohorts of dogs: healthy, intracranial neoplasia, and MUE. Using the learned peptide patterns for these three cohorts, classification prediction was evaluated for the same groups using a 10-fold cross validation methodology. Accuracy for classification was 100%, as well as 100% specific and 100% sensitive. This pilot study demonstrates that immunosignature profiles may help serve as a minimally invasive tool to distinguish between MUE and intracranial neoplasia in dogs.

Highlights

Immunosignature Differentiation of Meningoencephalomyelitis and Intracranial Neoplasia disorders, but it is rarely performed due to associated financial cost and patient risk. [1, 4, 12] What is needed is a reliable, replicated, non-invasive method that can distinguish between meningoencephalomyelitis of unknown etiology (MUE) and intracranial neoplasia in dogs
(15) In this study, we evaluated the capability of the immunosignature to differentiate MUE from intracranial neoplasia in dogs by measuring its sensitivity, specificity and accuracy
Criteria for inclusion in the MUE group included examination by a board-certified neurologist, clinical signs of intracranial disease, brain MRI findings compatible with described MUE variants including granulomatous meningoencephalitis (GME), necrotizing meningoencephalitis (NME), or necrotizing leukoencephalitis (NLE), and albuminocytologic dissociation or pleocytosis documented on CSF analysis.[21,22,23] Dogs with clinicopathologic or imaging features displaying overlap between GME, NME, and NLE were assigned diagnoses of MUE.[3]

Summary

Introduction

A variety of infectious, noninfectious, vascular, demyelinating and neoplastic disorders of the central nervous system (CNS) are recognized in dogs. [1,2,3,4] Serology and PCR remain effective tools in humans and canines for screening many of the infectious causes. [5,6,7,8] For many of the remaining non-neoplastic disorders, underlying inflammation associated with an immunologic disturbance is thought to be the basis for their pathogenesis. [2, 3] Often the initiating cause of the inflammation remains unknown and these cases are referred to as meningoencephalomyelitis of unknown etiology (MUE). [2, 3] MUE has been classically described as a disease that occurs in several types of small purebred dogs, but atypical forms have been identified in a variety of dog breeds. [9] These atypical MUE presentations are the most problematic to the diagnostician. [1, 4, 12] What is needed is a reliable, replicated, non-invasive method that can distinguish between MUE and intracranial neoplasia in dogs. Towards this goal, blood immunosignature peptide profiles have shown great promise in distinguishing between various disease states in human studies. Immunosignaturing works only after training with patients who have known diseases so that machine learning algorithms can identify underlying protein binding patterns in the microarray chip.

Methods

Results

Conclusion