No Cover Image

Journal article 531 views 164 downloads

Digital Pathology Identifies Associations between Tissue Inflammatory Biomarkers and Multiple Sclerosis Outcomes

Ben Cooze, James Neal, ALKA VINEED, J. C. Oliveira Orcid Logo, Lauren Griffiths, Kelsey Allen, KRISTEN HAWKINS, HTOO YADANAR, KRISJANIS GERHARDS, Ildiko Farkas, Richard Reynolds Orcid Logo, Owain Howell Orcid Logo

Cells, Volume: 13, Issue: 12, Start page: 1020

Swansea University Authors: Ben Cooze, James Neal, ALKA VINEED, Lauren Griffiths, Kelsey Allen, KRISTEN HAWKINS, HTOO YADANAR, KRISJANIS GERHARDS, Owain Howell Orcid Logo

  • 68904.VoR.pdf

    PDF | Version of Record

    © 2024 by the authors. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.

    Download (4.49MB)

Check full text

DOI (Published version): 10.3390/cells13121020

Abstract

Background: Multiple sclerosis (MS) is a clinically heterogeneous disease underpinned by inflammatory, demyelinating and neurodegenerative processes, the extent of which varies between individuals and over the course of the disease. Recognising the clinicopathological features that most strongly ass...

Full description

Published in: Cells
ISSN: 2073-4409
Published: MDPI AG 2024
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa68904
Abstract: Background: Multiple sclerosis (MS) is a clinically heterogeneous disease underpinned by inflammatory, demyelinating and neurodegenerative processes, the extent of which varies between individuals and over the course of the disease. Recognising the clinicopathological features that most strongly associate with disease outcomes will inform future efforts at patient phenotyping. Aims: We used a digital pathology workflow, involving high-resolution image acquisition of immunostained slides and opensource software for quantification, to investigate the relationship between clinical and neuropathological features in an autopsy cohort of progressive MS. Methods: Sequential sections of frontal, cingulate and occipital cortex, thalamus, brain stem (pons) and cerebellum including dentate nucleus (n = 35 progressive MS, females = 28, males = 7; age died = 53.5 years; range 38–98 years) were immunostained for myelin (anti-MOG), neurons (anti-HuC/D) and microglia/macrophages (anti-HLA). The extent of demyelination, neurodegeneration, the presence of active and/or chronic active lesions and quantification of brain and leptomeningeal inflammation was captured by digital pathology. Results: Digital analysis of tissue sections revealed the variable extent of pathology that characterises progressive MS. Microglia/macrophage activation, if found at a higher level in a single block, was typically elevated across all sampled blocks. Compartmentalised (perivascular/leptomeningeal) inflammation was associated with age-related measures of disease severity and an earlier death. Conclusion: Digital pathology identified prognostically important clinicopathological correlations in MS. This methodology can be used to prioritise the principal pathological processes that need to be captured by future MS biomarkers.
Keywords: digital pathology; multiple sclerosis; prognostic; progression
College: Faculty of Medicine, Health and Life Sciences
Funders: This work was supported in part by funds from the UK Multiple Sclerosis Society, the Research Wales Innovation Fund, Swansea University Research Excellence Scholarship (SURES) and the BRAIN Unit Infrastructure Award (Grant no: UA05; funded by Welsh Government through Health and Care Research Wales). United Kingdom Multiple Sclerosis Society Tissue Bank is funded by the Multiple Sclerosis Society of Great Britain and Northern Ireland reg.charity 207495.
Issue: 12
Start Page: 1020