Literature DB >> 25583839

Analysis of genes, pathways and networks involved in disease severity and age at onset in primary-progressive multiple sclerosis.

G Giacalone1, F Clarelli2, A M Osiceanu2, C Guaschino1, P Brambilla2, M Sorosina2, G Liberatore1, A Zauli2, F Esposito1, M Rodegher3, A Ghezzi4, D Galimberti5, F Patti6, N Barizzone7, F Guerini8, V Martinelli3, M Leone9, G Comi1, S D'Alfonso9, F Martinelli Boneschi10.   

Abstract

BACKGROUND: The role of genetic factors in influencing the clinical expression of multiple sclerosis (MS) is unclear.
OBJECTIVE: The objective of this paper is to identify genes, pathways and networks implicated in age at onset (AAO) and severity, measured using the Multiple Sclerosis Severity Score (MSSS), of primary-progressive MS (PPMS).
METHODS: We conducted a genome-wide association study (GWAS) of 470 PPMS patients of Italian origin:. Allelic association of 296,589 SNPs with AAO and MSSS was calculated. Pathway and network analyses were also conducted using different tools.
RESULTS: No single association signal exceeded genome-wide significance in AAO and MSSS analyses. Nominally associated genes to AAO and MSSS were enriched in both traits for 10 pathways, including: "oxidative phosphorylation" (FDRAAO=9*10(-4); FDRMSSS=3.0*10(-2)), "citrate (TCA) cycle" (FDRAAO=1.6*10(-2); FDRMSSS=3.2*10(-3)), and "B cell receptor signaling" (FDRAAO=3.1*10(-2); FDRMSSS=2.2*10(-3)). In addition, an enrichment of "chemokine signaling pathway" (FDR=9*10(-4)) for AAO and of "leukocyte transendothelial migration" (FDR=2.4*10(-3)) for MSSS trait was observed, among others. Network analysis revealed that p53 and CREB1 were central hubs for AAO and MSSS traits, respectively.
CONCLUSIONS: Despite the fact that no major effect signals emerged in the present GWAS, our data suggest that genetic variants acting in the context of oxidative stress and immune dysfunction could modulate the onset and severity of PPMS.
© The Author(s), 2015.

Entities:  

Keywords:  GWAS; age at onset; multiple sclerosis; network analysis; pathway analysis; primary-progressive; severity

Mesh:

Year:  2015        PMID: 25583839     DOI: 10.1177/1352458514564590

Source DB:  PubMed          Journal:  Mult Scler        ISSN: 1352-4585            Impact factor:   6.312


  2 in total

1.  Response to interferon-beta treatment in multiple sclerosis patients: a genome-wide association study.

Authors:  S Mahurkar; M Moldovan; V Suppiah; M Sorosina; F Clarelli; G Liberatore; S Malhotra; X Montalban; A Antigüedad; M Krupa; V G Jokubaitis; F C McKay; P N Gatt; M J Fabis-Pedrini; V Martinelli; G Comi; J Lechner-Scott; A G Kermode; M Slee; B V Taylor; K Vandenbroeck; M Comabella; F M Boneschi; C King
Journal:  Pharmacogenomics J       Date:  2016-03-22       Impact factor: 3.550

2.  The gut microbiota in pediatric multiple sclerosis and demyelinating syndromes.

Authors:  Helen Tremlett; Feng Zhu; Douglas Arnold; Amit Bar-Or; Charles N Bernstein; Christine Bonner; Jessica D Forbes; Morag Graham; Janace Hart; Natalie C Knox; Ruth Ann Marrie; Ali I Mirza; Julia O'Mahony; Gary Van Domselaar; E Ann Yeh; Yinshan Zhao; Brenda Banwell; Emmanuelle Waubant
Journal:  Ann Clin Transl Neurol       Date:  2021-12-09       Impact factor: 4.511

  2 in total

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