In multiple sclerosis (MS), the most common neurological disease in the working young, inflammatory cells infiltrate the central nervous system (CNS) and attack the myelin-producing cells that are crucial for function and survival of axons. Most patients experience a relapsing-remitting disease course with ever worsening neurological symptoms and, ultimately, disability. Current diagnostic imaging techniques cannot predict relapses because they cannot detect the active leukocyte infiltration into the CNS that leads to clinical disease symptoms downstream. This proposal intends to provide a method that enables non-invasive assessment of this asymptomatic disease activity based on the detection of leukocyte-endothelial interaction (LEI) in the retina by live imaging, which will allow prediction of MS relapses and rapid feedback on treatment response and disease progression. Thus, retinal LEI detection could help transform therapeutic intervention in MS and mitigate the development and severity of disability in MS. LEI, the rolling of white blood cells that is a requirement for leukocyte infiltration, is absent in healthy CNS and considered a hallmark of inflammation. We hypothesize that retinal LEI near the optic nerve head (ONH) indicates active leukocyte infiltration into the CNS that precedes MRI detectable lesions and clinical disease symptoms. The retina is an optically accessible compartment of the CNS that lends itself to optical, intravital imaging through the pupil of the eye. With a scanning laser ophthalmoscope (SLO), custom built for mouse retinal imaging, retinal LEI was detected in early stages of experimental autoimmune encephalomyelitis (EAE), an accepted rodent model of MS, prior to clinical symptoms. Our preliminary data further demonstrated, that pro-inflammatory messengers can reach the retina via transport of cerebrospinal fluid (CSF) and cause retinal LEI, although the retina and optic nerve themselves are not inflamed.
In aim 1, we will characterize retinal LEI in EAE and compare its time course to that of leukocyte infiltration into the CNS, as assessed by flow cytometric analysis, and to development of CNS lesions by MRI. Treatment will be administered upon LEI detection and the disease time course compared with untreated controls.
In aim 2, we will assess the sensitivity of retinal LEI to remotely detect CNS inflammation. We determine if the location of an inflammatory brain lesion affects the frequency of retinal LEI. Furthermore, MS-relevant cytokines will be injected directly into the CSF to test their ability to elicit retinal LEI.
In aim 3, we will develop an adaptive optics (AO) SLO that is specialized for the detection of retinal LEI. Using high-speed scanning and a woofer-tweeter AO architecture, the instrument will generate a field of view that probes the area in and near the optic nerve head, where most LEI would be expected. This cutting-edge instrument will be used in a pilot study to assess retinal LEI in MS patients.

Public Health Relevance

This proposal aims to develop optical imaging of rolling white blood cells in the blood vessels of the retina as a marker for active inflammation in multiple sclerosis (MS) that current imaging methods cannot assess yet that could predict disease relapse. The marker will be characterized in mouse models of neuroinflammation and compared to accepted measures of brain inflammation, such as detection of brain lesions in magnetic resonance imaging and flow cytometric analysis of brain leukocyte infiltration. In addition, we will set up a specialized adaptive optics scanning laser ophthalmoscope for retinal imaging in MS patients, seeking to validate the marker in a small pilot study.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Research Project (R01)
Project #
5R01NS099431-04
Application #
9975233
Study Section
Medical Imaging Study Section (MEDI)
Program Officer
Utz, Ursula
Project Start
2017-08-15
Project End
2022-12-31
Budget Start
2021-01-01
Budget End
2021-12-31
Support Year
4
Fiscal Year
2021
Total Cost
Indirect Cost
Name
Massachusetts General Hospital
Department
Type
DUNS #
073130411
City
Boston
State
MA
Country
United States
Zip Code
02114