Immunophenotyping predictive of Mycoplasma infection in patients with chronic fatigue syndrome

Nijs, Jo, Coomans, Danny, Nicolson, Garth L., De Becker, Pascale, Christian, Demanet, and De Meirleir, Kenny (2003) Immunophenotyping predictive of Mycoplasma infection in patients with chronic fatigue syndrome. Journal of Chronic Fatigue Syndrome, 11 (2). pp. 51-69.

[img] PDF (Published Version) - Published Version
Restricted to Repository staff only

View at Publisher Website: http://dx.doi.org/10.1300/J092v11n02_05
 
1


Abstract

An impaired immune system and opportunistic infections are considered important characteristics in the pathophysiology of Chronic Fatigue Syndrome (CFS). Using immunofluorescence we examined healthy subjects (N = 35) and two subsets of CFS patients: those without evidence of Mycoplasma (N = 55) and those with evidence of a Myco-plasma infection in their blood (N = 131). Using monoclonal antibodies and forensic polymerase chain reaction for detection of M. hominis, M. fermentans, M. pneumoniae and M. penetrans, we examined leukocytes in peripheral blood samples. Both patient groups presented with significantly elevated CD25+ (activated) cells as compared to healthy volunteers. CFS patients without evidence of mycoplasma infection(s) had increased amounts of CD5+ B-cells. Stepwise discriminant analysis indicated the number of activated cells, number of memory CD4+ cells and percentage of suppressor T-cells (lower in Mycoplasma+ patients as compared to Mycoplasma- patients) as the discriminant variables. A classification tree, for predicting the presence of Mycoplasma species in CFS patients, was constructed. Taken together, these data confirm earlier reports on immune activation among CFS patients, but this does not appear to be specific for Mycoplasma-infected CFS patients.

Item ID: 6545
Item Type: Article (Research - C1)
ISSN: 1547-0660
Keywords: chronic fatigue syndrome; Mycoplasma; immunity; immunofluorescence
Date Deposited: 13 Oct 2010 01:25
FoR Codes: 01 MATHEMATICAL SCIENCES > 0104 Statistics > 010401 Applied Statistics @ 100%
SEO Codes: 92 HEALTH > 9299 Other Health > 929999 Health not elsewhere classified @ 100%
Downloads: Total: 1
More Statistics

Actions (Repository Staff Only)

Item Control Page Item Control Page