eprintid: 10056834
rev_number: 20
eprint_status: archive
userid: 608
dir: disk0/10/05/68/34
datestamp: 2018-09-24 08:17:28
lastmod: 2021-10-24 23:23:27
status_changed: 2018-09-24 08:17:28
type: article
metadata_visibility: show
creators_name: Herman, S
creators_name: Khoonsari, PE
creators_name: Tolf, A
creators_name: Steinmetz, J
creators_name: Zetterberg, H
creators_name: Åkerfeldt, T
creators_name: Jakobsson, P-J
creators_name: Larsson, A
creators_name: Spjuth, O
creators_name: Burman, J
creators_name: Kultima, K
title: Integration of magnetic resonance imaging and protein and metabolite CSF measurements to enable early diagnosis of secondary progressive multiple sclerosis
ispublished: pub
divisions: UCL
divisions: B02
divisions: C07
divisions: D07
divisions: F86
keywords: biomarker, data integration, disease progression, metabolomics, multiple sclerosis
note: This is an open access article distributed under the terms of the Creative Commons Attribution (CC BY-NC) license (https://creativecommons.org/licenses/by-nc/4.0/). See http://ivyspring.com/terms for full terms and conditions.
abstract: Molecular networks in neurological diseases are complex. Despite this fact, contemporary biomarkers are in most cases interpreted in isolation, leading to a significant loss of information and power. We present an analytical approach to scrutinize and combine information from biomarkers originating from multiple sources with the aim of discovering a condensed set of biomarkers that in combination could distinguish the progressive degenerative phenotype of multiple sclerosis (SPMS) from the relapsing-remitting phenotype (RRMS). Methods: Clinical and magnetic resonance imaging (MRI) data were integrated with data from protein and metabolite measurements of cerebrospinal fluid, and a method was developed to sift through all the variables to establish a small set of highly informative measurements. This prospective study included 16 SPMS patients, 30 RRMS patients and 10 controls. Protein concentrations were quantitated with multiplexed fluorescent bead-based immunoassays and ELISA. The metabolome was recorded using liquid chromatography-mass spectrometry. Clinical follow-up data of the SPMS patients were used to assess disease progression and development of disability. Results: Eleven variables were in combination able to distinguish SPMS from RRMS patients with high confidence superior to any single measurement. The identified variables consisted of three MRI variables: the size of the spinal cord and the third ventricle and the total number of T1 hypointense lesions; six proteins: galectin-9, monocyte chemoattractant protein-1 (MCP-1), transforming growth factor alpha (TGF-α), tumor necrosis factor alpha (TNF-α), soluble CD40L (sCD40L) and platelet-derived growth factor AA (PDGF-AA); and two metabolites: 20β-dihydrocortisol (20β-DHF) and indolepyruvate. The proteins myelin basic protein (MBP) and macrophage-derived chemokine (MDC), as well as the metabolites 20β-DHF and 5,6-dihydroxyprostaglandin F1a (5,6-DH-PGF1), were identified as potential biomarkers of disability progression. Conclusion: Our study demonstrates, in a limited but well-defined and data-rich cohort, the importance and value of combining multiple biomarkers to aid diagnostics and track disease progression.
date: 2018
date_type: published
official_url: http://dx.doi.org/10.7150/thno.26249
oa_status: green
full_text_type: pub
pmcid: PMC6134925
language: eng
primo: open
primo_central: open_green
article_type_text: Journal Article
verified: verified_manual
elements_id: 1583021
doi: 10.7150/thno.26249
pii: thnov08p4477
lyricists_name: Zetterberg, Henrik
lyricists_id: HZETT94
actors_name: Bracey, Alan
actors_id: ABBRA90
actors_role: owner
full_text_status: public
publication: Theranostics
volume: 8
number: 16
pagerange: 4477-4490
event_location: Australia
issn: 1838-7640
citation:        Herman, S;    Khoonsari, PE;    Tolf, A;    Steinmetz, J;    Zetterberg, H;    Åkerfeldt, T;    Jakobsson, P-J;                 ... Kultima, K; + view all <#>        Herman, S;  Khoonsari, PE;  Tolf, A;  Steinmetz, J;  Zetterberg, H;  Åkerfeldt, T;  Jakobsson, P-J;  Larsson, A;  Spjuth, O;  Burman, J;  Kultima, K;   - view fewer <#>    (2018)    Integration of magnetic resonance imaging and protein and metabolite CSF measurements to enable early diagnosis of secondary progressive multiple sclerosis.                   Theranostics , 8  (16)   pp. 4477-4490.    10.7150/thno.26249 <https://doi.org/10.7150/thno.26249>.       Green open access   
 
document_url: https://discovery.ucl.ac.uk/id/eprint/10056834/1/v08p4477.pdf