Literature DB >> 33452402

Quantitative MRI phenotypes capture biological heterogeneity in multiple sclerosis patients.

Ide Smets1,2,3, An Goris4,5, Marijne Vandebergh1,2, Jelle Demeestere3, Stefan Sunaert2,6, Patrick Dupont2,7, Bénédicte Dubois1,2,3.   

Abstract

Magnetization transfer ratio (MTR) and brain volumetric imaging are (semi-)quantitative MRI markers capturing demyelination, axonal degeneration and/or inflammation. However, factors shaping variation in these traits are largely unknown. In this study, we collected a longitudinal cohort of 33 multiple sclerosis (MS) patients and extended it cross-sectionally to 213. We measured MTR in lesions, normal-appearing white matter (NAWM), normal-appearing grey matter (NAGM) and total brain, grey matter, white matter and lesion volume. We also calculated the polygenic MS risk score. Longitudinally, inter-patient differences at inclusion and intra-patient changes during follow-up together explained > 70% of variance in MRI, with inter-patient differences at inclusion being the predominant source of variance. Cross-sectionally, we observed a moderate correlation of MTR between NAGM and NAWM and, less pronounced, with lesions. Age and gender explained about 30% of variance in total brain and grey matter volume. However, they contributed less than 10% to variance in MTR measures. There were no significant associations between MRI traits and the genetic risk score. In conclusion, (semi-)quantitative MRI traits change with ongoing disease activity but this change is modest in comparison to pre-existing inter-patient differences. These traits reflect individual variation in biological processes, which appear different from those involved in genetic MS susceptibility.

Entities:  

Year:  2021        PMID: 33452402      PMCID: PMC7811013          DOI: 10.1038/s41598-021-81035-8

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


  45 in total

1.  Brain damage as detected by magnetization transfer imaging is less pronounced in benign than in early relapsing multiple sclerosis.

Authors:  Nicola De Stefano; Marco Battaglini; M L Stromillo; Valentina Zipoli; M L Bartolozzi; Leonello Guidi; Gianfranco Siracusa; Emilio Portaccio; Antonio Giorgio; Sandro Sorbi; Antonio Federico; Maria Pia Amato
Journal:  Brain       Date:  2006-06-30       Impact factor: 13.501

2.  Intra- and interscanner variability of magnetic resonance imaging based volumetry in multiple sclerosis.

Authors:  Viola Biberacher; Paul Schmidt; Anisha Keshavan; Christine C Boucard; Ruthger Righart; Philipp Sämann; Christine Preibisch; Daniel Fröbel; Lilian Aly; Bernhard Hemmer; Claus Zimmer; Roland G Henry; Mark Mühlau
Journal:  Neuroimage       Date:  2016-07-16       Impact factor: 6.556

3.  Age and gender effects on human brain anatomy: a voxel-based morphometric study in healthy elderly.

Authors:  Charles D Smith; Himachandra Chebrolu; David R Wekstein; Frederick A Schmitt; William R Markesbery
Journal:  Neurobiol Aging       Date:  2006-06-13       Impact factor: 4.673

4.  HLA-DRB1*15 influences the development of brain tissue damage in early PPMS.

Authors:  Carmen Tur; Sreeram Ramagopalan; Daniel R Altmann; Benedetta Bodini; Mara Cercignani; Zhaleh Khaleeli; David H Miller; Alan J Thompson; Olga Ciccarelli
Journal:  Neurology       Date:  2014-10-08       Impact factor: 9.910

5.  Conventional and magnetization transfer MRI predictors of clinical multiple sclerosis evolution: a medium-term follow-up study.

Authors:  Marco Rovaris; Federica Agosta; Maria Pia Sormani; Matilde Inglese; Vittorio Martinelli; Giancarlo Comi; Massimo Filippi
Journal:  Brain       Date:  2003-08-22       Impact factor: 13.501

6.  Diagnostic criteria for multiple sclerosis: 2010 revisions to the McDonald criteria.

Authors:  Chris H Polman; Stephen C Reingold; Brenda Banwell; Michel Clanet; Jeffrey A Cohen; Massimo Filippi; Kazuo Fujihara; Eva Havrdova; Michael Hutchinson; Ludwig Kappos; Fred D Lublin; Xavier Montalban; Paul O'Connor; Magnhild Sandberg-Wollheim; Alan J Thompson; Emmanuelle Waubant; Brian Weinshenker; Jerry S Wolinsky
Journal:  Ann Neurol       Date:  2011-02       Impact factor: 10.422

7.  Loss of 'homeostatic' microglia and patterns of their activation in active multiple sclerosis.

Authors:  Tobias Zrzavy; Simon Hametner; Isabella Wimmer; Oleg Butovsky; Howard L Weiner; Hans Lassmann
Journal:  Brain       Date:  2017-07-01       Impact factor: 13.501

8.  Age independently affects myelin integrity as detected by magnetization transfer magnetic resonance imaging in multiple sclerosis.

Authors:  R D Newbould; R Nicholas; C L Thomas; R Quest; J S Z Lee; L Honeyfield; A Colasanti; O Malik; M Mattoscio; P M Matthews; M P Sormani; A D Waldman; P A Muraro
Journal:  Neuroimage Clin       Date:  2014-03-31       Impact factor: 4.881

9.  Magnetization transfer ratio and myelin in postmortem multiple sclerosis brain.

Authors:  Klaus Schmierer; Francesco Scaravilli; Daniel R Altmann; Gareth J Barker; David H Miller
Journal:  Ann Neurol       Date:  2004-09       Impact factor: 10.422

10.  Imputing amino acid polymorphisms in human leukocyte antigens.

Authors:  Xiaoming Jia; Buhm Han; Suna Onengut-Gumuscu; Wei-Min Chen; Patrick J Concannon; Stephen S Rich; Soumya Raychaudhuri; Paul I W de Bakker
Journal:  PLoS One       Date:  2013-06-06       Impact factor: 3.240

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