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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

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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...

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Published in: Cells
ISSN: 2073-4409
Published: MDPI AG 2024
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URI: https://cronfa.swan.ac.uk/Record/cronfa68904
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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&#x2013;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.</abstract><type>Journal Article</type><journal>Cells</journal><volume>13</volume><journalNumber>12</journalNumber><paginationStart>1020</paginationStart><paginationEnd/><publisher>MDPI AG</publisher><placeOfPublication/><isbnPrint/><isbnElectronic/><issnPrint/><issnElectronic>2073-4409</issnElectronic><keywords>digital pathology; multiple sclerosis; prognostic; progression</keywords><publishedDay>11</publishedDay><publishedMonth>6</publishedMonth><publishedYear>2024</publishedYear><publishedDate>2024-06-11</publishedDate><doi>10.3390/cells13121020</doi><url/><notes/><college>COLLEGE NANME</college><department>Medical School</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>MEDS</DepartmentCode><institution>Swansea University</institution><apcterm>Other</apcterm><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.</funders><projectreference/><lastEdited>2025-03-25T14:15:13.5638508</lastEdited><Created>2025-02-17T14:39:21.2144811</Created><path><level id="1">Faculty of Medicine, Health and Life Sciences</level><level id="2">Swansea University Medical School - Biomedical Science</level></path><authors><author><firstname>Ben</firstname><surname>Cooze</surname><order>1</order></author><author><firstname>James</firstname><surname>Neal</surname><order>2</order></author><author><firstname>ALKA</firstname><surname>VINEED</surname><order>3</order></author><author><firstname>J. 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spelling 2025-03-25T14:15:13.5638508 v2 68904 2025-02-17 Digital Pathology Identifies Associations between Tissue Inflammatory Biomarkers and Multiple Sclerosis Outcomes 785346ffc3dae14c560e63727f4017d3 Ben Cooze Ben Cooze true false 3d905ecd4df7a2ee050a8804c1140de1 James Neal James Neal true false 98bf639834abef8e75cbc497e5e96410 ALKA VINEED ALKA VINEED true false 8811c280da03bf66352d97f756e91ae1 Lauren Griffiths Lauren Griffiths true false a57a44d79880dac72cd792a77a31851c Kelsey Allen Kelsey Allen true false 4d68c146dfb2c32f9f2a8c515cefd01f KRISTEN HAWKINS KRISTEN HAWKINS true false 1740d3181d7348e88b928e6f70abb3d4 HTOO YADANAR HTOO YADANAR true false bfb12b5f2a064ead1cb61fc11540cd72 KRISJANIS GERHARDS KRISJANIS GERHARDS true false 58c995486fc93a242b987640b692db8c 0000-0003-2157-9157 Owain Howell Owain Howell true false 2025-02-17 MEDS 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. Journal Article Cells 13 12 1020 MDPI AG 2073-4409 digital pathology; multiple sclerosis; prognostic; progression 11 6 2024 2024-06-11 10.3390/cells13121020 COLLEGE NANME Medical School COLLEGE CODE MEDS Swansea University Other 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. 2025-03-25T14:15:13.5638508 2025-02-17T14:39:21.2144811 Faculty of Medicine, Health and Life Sciences Swansea University Medical School - Biomedical Science Ben Cooze 1 James Neal 2 ALKA VINEED 3 J. C. Oliveira 0009-0006-4908-2360 4 Lauren Griffiths 5 Kelsey Allen 6 KRISTEN HAWKINS 7 HTOO YADANAR 8 KRISJANIS GERHARDS 9 Ildiko Farkas 10 Richard Reynolds 0000-0003-4622-4694 11 Owain Howell 0000-0003-2157-9157 12 68904__33879__5d6183aaacbd4b71b2206f1e923b5b7f.pdf 68904.VoR.pdf 2025-03-25T14:13:07.1286134 Output 4705764 application/pdf Version of Record true © 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. true eng https:// creativecommons.org/licenses/by/ 4.0/
title Digital Pathology Identifies Associations between Tissue Inflammatory Biomarkers and Multiple Sclerosis Outcomes
spellingShingle Digital Pathology Identifies Associations between Tissue Inflammatory Biomarkers and Multiple Sclerosis Outcomes
Ben Cooze
James Neal
ALKA VINEED
Lauren Griffiths
Kelsey Allen
KRISTEN HAWKINS
HTOO YADANAR
KRISJANIS GERHARDS
Owain Howell
title_short Digital Pathology Identifies Associations between Tissue Inflammatory Biomarkers and Multiple Sclerosis Outcomes
title_full Digital Pathology Identifies Associations between Tissue Inflammatory Biomarkers and Multiple Sclerosis Outcomes
title_fullStr Digital Pathology Identifies Associations between Tissue Inflammatory Biomarkers and Multiple Sclerosis Outcomes
title_full_unstemmed Digital Pathology Identifies Associations between Tissue Inflammatory Biomarkers and Multiple Sclerosis Outcomes
title_sort Digital Pathology Identifies Associations between Tissue Inflammatory Biomarkers and Multiple Sclerosis Outcomes
author_id_str_mv 785346ffc3dae14c560e63727f4017d3
3d905ecd4df7a2ee050a8804c1140de1
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8811c280da03bf66352d97f756e91ae1
a57a44d79880dac72cd792a77a31851c
4d68c146dfb2c32f9f2a8c515cefd01f
1740d3181d7348e88b928e6f70abb3d4
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author_id_fullname_str_mv 785346ffc3dae14c560e63727f4017d3_***_Ben Cooze
3d905ecd4df7a2ee050a8804c1140de1_***_James Neal
98bf639834abef8e75cbc497e5e96410_***_ALKA VINEED
8811c280da03bf66352d97f756e91ae1_***_Lauren Griffiths
a57a44d79880dac72cd792a77a31851c_***_Kelsey Allen
4d68c146dfb2c32f9f2a8c515cefd01f_***_KRISTEN HAWKINS
1740d3181d7348e88b928e6f70abb3d4_***_HTOO YADANAR
bfb12b5f2a064ead1cb61fc11540cd72_***_KRISJANIS GERHARDS
58c995486fc93a242b987640b692db8c_***_Owain Howell
author Ben Cooze
James Neal
ALKA VINEED
Lauren Griffiths
Kelsey Allen
KRISTEN HAWKINS
HTOO YADANAR
KRISJANIS GERHARDS
Owain Howell
author2 Ben Cooze
James Neal
ALKA VINEED
J. C. Oliveira
Lauren Griffiths
Kelsey Allen
KRISTEN HAWKINS
HTOO YADANAR
KRISJANIS GERHARDS
Ildiko Farkas
Richard Reynolds
Owain Howell
format Journal article
container_title Cells
container_volume 13
container_issue 12
container_start_page 1020
publishDate 2024
institution Swansea University
issn 2073-4409
doi_str_mv 10.3390/cells13121020
publisher MDPI AG
college_str Faculty of Medicine, Health and Life Sciences
hierarchytype
hierarchy_top_id facultyofmedicinehealthandlifesciences
hierarchy_top_title Faculty of Medicine, Health and Life Sciences
hierarchy_parent_id facultyofmedicinehealthandlifesciences
hierarchy_parent_title Faculty of Medicine, Health and Life Sciences
department_str Swansea University Medical School - Biomedical Science{{{_:::_}}}Faculty of Medicine, Health and Life Sciences{{{_:::_}}}Swansea University Medical School - Biomedical Science
document_store_str 1
active_str 0
description 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.
published_date 2024-06-11T05:22:05Z
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score 11.089572

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