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Review
. 2013 Apr 9;8(4):e61110.
doi: 10.1371/journal.pone.0061110. Print 2013.

Systematic review and meta-analysis of the sero-epidemiological association between Epstein Barr virus and multiple sclerosis

Affiliations
Review

Systematic review and meta-analysis of the sero-epidemiological association between Epstein Barr virus and multiple sclerosis

Yahya H Almohmeed et al. PLoS One. .

Abstract

Background: A role for Epstein Barr virus (EBV) in multiple sclerosis (MS) has been postulated. Previous systematic reviews found higher prevalences of anti-EBV antibodies in MS patients compared to controls, but many studies have since been published, and there is a need to apply more rigorous systematic review methods.

Methodology/principal findings: We examined the link between EBV and MS by conducting a systematic review and meta-analysis of case-control and cohort studies that examined the prevalence of anti-EBV antibodies in the serum of cases and controls. We searched Medline and Embase databases from 1960 to 2012, with no language restriction. The Mantel-Haenszel odds ratios (OR) for anti-EBV antibodies sero-positivity were calculated, and meta-analysis conducted. Quality assessment was performed using a modified version of the Newcastle Ottawa scale. Thirty-nine studies were included. Quality assessment found most studies reported acceptable selection and comparability of cases and controls. However the majority had poor reporting of ascertainment of exposure. Most studies found a higher sero-prevalence of anti-EBNA IgG and anti-VCA IgG in cases compared to controls. The results for anti-EA IgG were mixed with only half the studies finding a higher sero-prevalence in cases. The meta-analysis showed a significant OR for sero-positivity to anti-EBNA IgG and anti-VCA IgG in MS cases (4.5 [95% confidence interval (CI) 3.3 to 6.6, p<0.00001] and 4.5 [95% CI 2.8 to 7.2, p<0.00001] respectively). However, funnel plot examination suggested publication bias for the reporting of the anti-EBNA IgG. No significant difference in the OR for sero-positivity to anti-EA IgG was found (1.4 [95% CI 0.9 to 2.1, p = 0.09]).

Conclusion/significance: These findings support previous systematic reviews, however publication bias cannot be excluded. The methodological conduct of studies could be improved, particularly with regard to reporting and conduct of laboratory analyses.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1. Studies identification in search strategy.
Adopted from PRISMA 2009 Flow Diagram (Moher, et al., 2009)*.
Figure 2
Figure 2. Forest plot of the Odds Ratio for anti-EBNA sero-positivity.
Figure 3
Figure 3. Funnel plot for studies testing for anti-EBNA IgG sero-positivity.
Figure 4
Figure 4. Forest plot of the Odds Ratio for anti-VCA IgG sero-positivity.
Figure 5
Figure 5. Funnel plot of studies testing for anti-VCA IgG sero-positivity.
Figure 6
Figure 6. Forest plot of the Odds Ratio for anti-EA IgG sero-positivity.
Note: the study Wagner, et al., (2000) in Figure 6 is an older version of the study Wandinger, et al., (2000).
Figure 7
Figure 7. Funnel plot of studies testing for anti-EA IgG sero-positivity.
Figure 8
Figure 8. Forest plot of the Odds ratio for anti-EBV IgG sero-negativity.

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