Literature DB >> 17538884

Gene expression correlates of postinfective fatigue syndrome after infectious mononucleosis.

Barbara Cameron1, Sally Galbraith, Yun Zhang, Tracey Davenport, Ute Vollmer-Conna, Denis Wakefield, Ian Hickie, William Dunsmuir, Toni Whistler, Suzanne Vernon, William C Reeves, Andrew R Lloyd.   

Abstract

BACKGROUND: Infectious mononucleosis (IM) commonly triggers a protracted postinfective fatigue syndrome (PIFS) of unknown pathogenesis.
METHODS: Seven subjects with PIFS with 6 or more months of disabling symptoms and 8 matched control subjects who had recovered promptly from documented IM were studied. The expression of 30,000 genes was examined in the peripheral blood by microarray analysis in 65 longitudinally collected samples. Gene expression patterns associated with PIFS were sought by correlation with symptom factor scores.
RESULTS: Differential expression of 733 genes was identified when samples collected early during the illness and at the late (recovered) time point were compared. Of these genes, 234 were found to be significantly correlated with the reported severity of the fatigue symptom factor, and 180 were found to be correlated with the musculoskeletal pain symptom factor. Validation by analysis of the longitudinal expression pattern revealed 35 genes for which changes in expression were consistent with the illness course. These genes included several that are involved in signal transduction pathways, metal ion binding, and ion channel activity.
CONCLUSIONS: Gene expression correlates of the cardinal symptoms of PIFS after IM have been identified. Further studies of these gene products may help to elucidate the pathogenesis of PIFS.

Entities:  

Mesh:

Year:  2007        PMID: 17538884     DOI: 10.1086/518614

Source DB:  PubMed          Journal:  J Infect Dis        ISSN: 0022-1899            Impact factor:   5.226


  6 in total

1.  Harnessing pain heterogeneity and RNA transcriptome to identify blood-based pain biomarkers: a novel correlational study design and bioinformatics approach in a graded chronic constriction injury model.

Authors:  Peter M Grace; Daniel Hurley; Daniel T Barratt; Anna Tsykin; Linda R Watkins; Paul E Rolan; Mark R Hutchinson
Journal:  J Neurochem       Date:  2012-07-09       Impact factor: 5.372

2.  A gene signature for post-infectious chronic fatigue syndrome.

Authors:  John W Gow; Suzanne Hagan; Pawel Herzyk; Celia Cannon; Peter O Behan; Abhijit Chaudhuri
Journal:  BMC Med Genomics       Date:  2009-06-25       Impact factor: 3.063

3.  The complexity of antibody-dependent enhancement of dengue virus infection.

Authors:  Maria G Guzman; Susana Vazquez
Journal:  Viruses       Date:  2010-12-08       Impact factor: 5.048

4.  The status of and future research into Myalgic Encephalomyelitis and Chronic Fatigue Syndrome: the need of accurate diagnosis, objective assessment, and acknowledging biological and clinical subgroups.

Authors:  Frank N M Twisk
Journal:  Front Physiol       Date:  2014-03-27       Impact factor: 4.566

5.  Long-term perturbation of the peripheral immune system months after SARS-CoV-2 infection.

Authors:  Feargal J Ryan; Christopher M Hope; Makutiro G Masavuli; Miriam A Lynn; Simon C Barry; Branka Grubor-Bauk; David J Lynn; Zelalem A Mekonnen; Arthur Eng Lip Yeow; Pablo Garcia-Valtanen; Zahraa Al-Delfi; Jason Gummow; Catherine Ferguson; Stephanie O'Connor; Benjamin A J Reddi; Pravin Hissaria; David Shaw; Chuan Kok-Lim; Jonathan M Gleadle; Michael R Beard
Journal:  BMC Med       Date:  2022-01-14       Impact factor: 8.775

6.  The International Collaborative on Fatigue Following Infection (COFFI).

Authors:  Ben Z Katz; Simon M Collin; Gabrielle Murphy; Rona Moss-Morris; Vegard Bruun Wyller; Knut-Arne Wensaas; Jeannine L A Hautvast; Chantal P Bleeker-Rovers; Ute Vollmer-Conna; Dedra Buchwald; Renée Taylor; Paul Little; Esther Crawley; Peter D White; Andrew Lloyd
Journal:  Fatigue       Date:  2018-01-19
  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.