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Association between Helicobacter pylori infection and multiple sclerosis: A systematic review and meta-analysis

Multiple Sclerosis and Related Disorders, May 2016, Pages 92 - 97



To investigate the association between Helicobacter pylori infection and multiple sclerosis.


A comprehensive search of the databases including PubMed/MEDLINE and EMBASE was performed from their dates of inception to January 2016. Inclusion criteria were the observational studies in adult assessing the association between Helicobacter pylori infection and multiple sclerosis. The main outcome was the prevalence of Helicobacter pylori infection comparing between participants with multiple sclerosis and controls. The between-study heterogeneity of effect-size was quantified using the Q statistic and I2.


The initial search yielded 103 articles. Seventeen articles underwent full-length review and data was extracted from six observational studies involving 1902 participants. There was a statistically significant lower odds Helicobacter pylori infection in multiple sclerosis with pooled odds ratio of 0.59 (95% CI: 0.37–0.94, P=0.03, I2=71%). We conducted a univariate meta-regression analysis to assess potential source of heterogeneity. Age of patient and age of onset of multiple sclerosis were significant predictors of association between Helicobacter pylori infection and multiple sclerosis (beta-coefficient =−0.23, SE=0.10, p=0.02 and beta-coefficient =−0.34, SE=0.17, p=0.04, respectively).


We demonstrate a significant lower prevalence of Helicobacter pylori infection in patients with multiple sclerosis. This pathogen might be a protective factor for developing multiple sclerosis.


  • Multiple sclerosis (MS) is the chronic autoimmune inflammatory of central nervous system.
  • Helicobacter pylori infection is associated with autoimmune diseases as it can provoke inflammatory response.
  • Our meta-analysis suggests a protective effect of Helicobacter pylori infection against the development of MS.

Abbreviations: Hp - Helicobacter pylori, HR - hazard ratio, ELISA - enzyme-linked immunosorbent assay, RUT - rapid urease test, UBT - 13C-urea breath test, MS - multiple sclerosis, NOS - Newcastle-Ottawa scale, OR - odd ratio, PCR - polymerase chain reaction, RR - relative risk.

Keywords: Helicobacter pylori, Multiple sclerosis, Meta-analysis, Observational studies, Systematic review.

1. Introduction

Multiple sclerosis (MS) is the chronic autoimmune inflammatory and neurodegenerative disorder of central nervous system (Grigoriadis and van Pesch, 2015). It affects around 400,000 people in the US and 2.5 million worldwide (Tullman, 2013). Despite of unclear etiology, MS likely results from the complex interactions between environmental and genetic factors. An exposure to number of environmental factors appear to influence for the developing of MS including ultraviolet exposure, vitamin D intake, smoking, certain viruses and bacteria (Milo and Kahana, 2010).

Helicobacter pylori (Hp) is the highly prevalent pathogen, which infects more than half of the populations worldwide (McColl, 2010). Majority of Hp infected individuals are asymptomatic, however, Hp can lead to gastritis, peptic ulcer disease, gastric mucosa-associated lymphoid tissue lymphoma and gastric adenocarcinoma (Suerbaum and Michetti, 2002 and Wotherspoon et al, 1991). Apart from those gastrointestinal manifestations, previous studies indicated the association between Hp infection and several autoimmune diseases that could be either positive association including systemic lupus erythematosus, rheumatoid arthritis, vasculitis, systemic sclerosis and sjögren's syndrome, or negative association including inflammatory bowel disease, eczema, asthma and allergic rhinitis (Hasni et al, 2011, Hasni, 2012, Luther et al, 2010, McCune et al, 2003, and Radic, 2014).

Several recent studies have been investigated the role of Hp as a potential environmental factor triggering immune dysregulation leading to MS. However, there are contradictory data showing negative (Li et al, 2009, Malli et al, 2015, Mohebi et al, 2013, and Pedrini et al, 2015), positive (Gavalas et al., 2015) and no correlations (Long et al., 2013) between Hp and MS. The pathogenic mechanism of this association could be explained by an ongoing antigen stimulation due to chronic Hp infection, which provokes inflammatory response and autoimmunity via various mechanisms including polyclonal activation, molecular mimicry, epitope spread, superantigens and bystander activation (Radic, 2014 and Seriolo et al, 2001). Hence, in light of the controversy, we conducted a systematic review with a meta-analysis of all published observational studies investigating the association of Hp infection and MS compared with non-MS individuals.

2. Materials and methods

This systematic review and meta-analysis was conducted and reported according to the Meta-analysis Of Observational Studies in Epidemiology statement (Stroup et al., 2000) and was registered in PROSPERO (registration number: CRD42015029295).

2.1. Data sources and search strategy

Two authors (AS, SU) independently searched published studies indexed in PubMed/MEDLINE and EMBASE from date of inception to January 2016. References of all selected studies were also examined. The following main search terms were used: Helicobacter pylori, H. pylori, Campylobacter pylori, and multiple sclerosis. The full search terms used were detailed in Item S1 in Supplementary Material.

2.2. Study Selection and data extraction

Our inclusion criteria were (1) published observational studies including cross-sectional, cohort, and case-control studies assessing the association between Hp infection and MS, (2) participants aged 18 years or older, (3) relative risks (RR), odds ratios (OR), hazard ratios (HR), standardized incidence ratios with 95% confidence intervals (CI) of the risk of Hp infection were provided, (4) participants without MS were used as a reference group. We excluded (1) review articles, case reports, abstracts, and unpublished studies, and (2) participants who had eradication of Hp.

Hp infection is diagnosed by means of the 13C-urea breath test (UBT), rapid urease test (RUT), polymerase chain reaction (PCR), histological assessment, or enzyme-linked immunosorbent assay (ELISA). At least one positive test result was regarded as confirmation of infection. MS was diagnosed by neurologist using the McDonald criteria, which was based on clinical presentations, finding on magnetic resonance imaging and cerebrospinal fluid profile (Polman et al., 2011).

Two authors (AS and SU) independently reviewed titles and abstracts of all citations that were identified. After all abstracts were reviewed, data comparisons between the two investigators were conducted to ensure completeness and reliability. The inclusion criteria were independently applied to all identified studies. Differing decisions were resolved by consensus between the two authors.

Full-text versions of potentially relevant papers identified in the initial screening were retrieved. If articles from the same study were found, only the article with the most complete data was included. Data concerning author, year of publication, study design, study location, participant characteristics, comorbidities, methods of Hp detection, diagnostic criteria of MS, factors adjusted in multivariate analysis, and outcome were independently extracted. We contacted the authors of the primary reports to request any unpublished data. If the authors did not reply, we used the available data for our analyses.

2.3. Assessment of quality

A subjective assessment of methodological quality for observational studies was evaluated by two authors (AS and SU) using the Newcastle-Ottawa Scale (NOS) (Stang, 2010). The NOS is a quality assessment tool for non-randomized studies. A total score of 3 or less was considered poor, 4-6 was considered moderate, and 7-9 was deemed high quality. We excluded poor quality study in the sensitivity analysis. Discrepant opinions between authors were resolved by consensus.

2.4. Statistical analysis

We performed meta-analysis of the included studies using Comprehensive Meta-Analysis 3.3 software from Biostat, Inc. We used random-effects model and calculated pooled effect estimate of MS with 95% confidence intervals (CI) comparing between group of MS and non-MS individuals. We used effect size (OR, HR, RR) from multivariate model with confounding factors adjusted in each study. We excluded studies from meta-analysis and only presented the result with narrative description when there were not sufficient comparable data available for outcome of interest. The heterogeneity of effect size estimates across these studies was quantified using the Q statistic, its p-value, and I2 (P<0.10 was considered significant). Subgroup analysis and meta-regression were performed to find the source of existing heterogeneity. Publication bias was assessed using funnel plot, Egger's regression test and its implications with the trim and fill method (Sterne and Egger, 2001).

3. Results

3.1. Description of included studies

The initial search yielded 103 articles (Fig. 1); 86 articles were excluded based on title and abstract review. A total of 17 articles underwent full-length review. Eleven articles were excluded because they were not observational studies (5 articles), did not have Hp information (4 articles), or did not have MS as an outcome (2 articles). A total of 6 studies (Li et al, 2009, Long et al, 2013, Mohebi et al, 2013, Gavalas et al, 2015, Malli et al, 2015, and Pedrini et al, 2015) involving 1902 participants were included in meta-analysis. The characteristics of the extracted studies included in this review are outlined in Table 1. The quality of included studies was moderate to high, ranged from 6 to 8.

Fig. 1

Fig. 1 Results of the information search.

Table 1 Characteristics of included studies.

Study Country Year Study design Total number (n) Cases Reference group Mean age of cases, years Female (%) Diagnosis of Hp infection Diagnosis of MS Quality assessment (Newcastle-Ottawa scale)
Li et al. (2009) Japan 2007 Case-control study 190 Patients who were diagnosed in Department of Neurology, Kyushu University Hospital N/A 46.9±13.2 76.3 Serology (ELISA) McDonald criteria, 2001 Selection: 3
Comparability: 2
Outcome: 2
Long et al. (2013) China 2012 Case-control study 69 As part of an MS/demyelinating disease database in the Department of Neurology, Hospital of Sun Yat Sen Healthy age-matched controls from a medical examination center 33.86±10.58 53.6 Serology (ELISA) N/A Selection: 4
Comparability: 1
Outcome: 3
Mohebi et al. (2013) Iran 2013 Case-control study 313 All patients who were diagnosed in Rasoul-Akram Hospital Non-MS ambulatory clinical patients 32±8 46 Serelogy (ELISA) McDonald criteria, 2001 Selection: 3
Comparability: 1
Outcome: 2
Gavalas et al. (2015) Greece 2015 Case-control study 64 Patients from Multiple Sclerosis Unit of the Neurology Department of “Papageorgiou” General Hospital of Thessaloniki. Age- and sex-matched individuals with mild iron deficiency anemia 38.05±1.3 71.9% Histology McDonald Criteria 2010, revised Selection: 4
Comparability: 1
Outcome: 2
Malli et al. (2015) India 2015 Case-control study 417 Patients from the Mangalore demyelinating disease registry Patients who visited the outpatient clinic with minor neurological complaints 36.56±11.95 66.2 Serelogy (ELISA) McDonald Criteria 2010, revised Selection: 4
Comparability: 1
Outcome: 2
Pedrini et al. (2015) Australia 2015 Case-control study 849 Caucasian patients enrolled into the Perth Demyelinating Disease Database Age- and sex-matched individuals from the Busselton Community Health Study 47.7±12.4 75 Serelogy (ELISA) McDonald criteria, 2001 Selection: 3
Comparability: 1
Outcome: 2

Abbreviation: ELISA: Enzyme-linked immunosorbent assay; Hp: Helicobacter pylori; MS: Multiple sclerosis; OR: Odd ratio.

3.2. Meta-analysis results

Six studies (all case-control studies (Li et al, 2009, Long et al, 2013, Mohebi et al, 2013, Gavalas et al, 2015, Malli et al, 2015, and Pedrini et al, 2015)) were included in the meta-analysis. There was a statistically significant lower odds of Hp infection in MS comparing with non-MS controls with pooled OR of 0.59 (95% CI: 0.37–0.94, P=0.03, I2=71%, Pheterogeneity=0.002) (Fig. 2).

Fig. 2

Fig. 2 Forest plot of pooled odd ratio of included studies comparing Helicobacter pylori infection in patients with multiple sclerosis and controls. CI, confidence interval.

3.3. Sensitivity analysis

We performed sensitivity analysis by removing one study at a time from meta-analysis. None of the results were significantly altered, indicating that our results were robust (Item S2).

3.4. Meta-regression

We conducted a univariate meta-regression analysis to assess potential source of heterogeneity. Age was a significant predictor of association between Hp infection and MS (beta-coefficient =−0.23, SE=0.10, p=0.02). Age of onset of MS was also a predictor (beta-coefficient =−0.34, SE=0.17, p=0.04).

3.5. Publication bias

To investigate potential publication bias, we examined the contour-enhanced funnel plot of the included studies that assessed OR of Hp (Fig. 3). Vertical axis represents study size (standard error by log odds ratio) while horizontal axis represents effect size (log odds ratio). The plot excludes bias since there is symmetrical distribution of studies on both sides of the mean. The Egger's test was non-significant (P=0.12). Using the trim and fill methods in the random-effects model, there was no difference of the imputed OR and its 95% CI.

Fig. 3

Fig. 3 Funnel plots showing publication bias in the studies reporting number of participants with Helicobacter pylori infection in patients with multiple sclerosis and controls. Circles represent observed published studies.

4. Discussion

This study is the first systematic review and meta-analysis of published observational studies assessing the association between Hp infection and MS. We demonstrated a significant lower prevalence of Hp infection among MS patients compared with sex- and age-matched non-MS controls with pooled OR of 0.50. Our meta-analysis suggests a potential protective effect of Hp infection against the development of MS.

This association could be explained by the mechanisms depicting conceptual framework for the hygiene hypothesis (Strachan, 1989). MS is the multi-factorial disease, however; autoimmunity is the most acceptable explanation (Grigoriadis and van Pesch, 2015). Hp antigen can affect the balance between T helper 1 and T helper 2 responses and it is also able to act as superantigens, selectively activation or deletion of specific T-cell subsets. Moreover, Hp antigen is also able to affect the production of interleukin 10, which has anti-allergic properties. Lastly, component of bacterial products may compete with other environmental antigens responsible for the atopic conditions (Cremonini and Gasbarrini, 2003). Hp infection was also found to be the protective factors for other autoimmune-related diseases including inflammatory bowel disease, asthma, eczema and allergic rhinitis that could be explained by similar pathogenic mechanisms (Luther et al, 2010 and McCune et al, 2003). Clinical applications of our finding, Hp might be the protective factor of MS, therefore, Hp pharmaceutical products can be the potential treatment in patients with MS. For example, Hp nanoparticles with neuro-specific targets might help in preventing MS without causing deteriorating effect of the organism while serving its therapeutic benefit (Pezeshki et al., 2008).

Our study has several strengths. First, we included all relevant observational studies by performing a comprehensive search of the MEDLINE and EMBASE databases. Second, two independent investigators performed data extraction, data analysis, and quality assessments of the methods. Consistency was checked by arbitrators, contributing to the accuracy of data in the meta-analysis. Third, all included studies were of moderate to high quality.

There are some limitations in this study. First, most of included studies used IgG serological antibodies as the diagnostic method for Hp. However, this test is known to have high sensitivity but low specificity giving high false positive rate and also low accuracy. Second, most studies were from the high-prevalence countries mainly from Asia (Peleteiro et al., 2014). Only two included studies are from low-prevalence area was from Greece and Australia (Gavalas et al, 2015 and Pedrini et al, 2015). Third, this is a meta-analysis of observational studies, which can only demonstrate an association, not causality. Fourth, statistical heterogeneity is present in this study. The possible sources of these heterogeneities include the differences in the study design, methodology and population.

In summary, our meta-analysis demonstrates significant negative association between Hp infection and MS. Further researches are warranted to conduct in prospective in nature, using higher specificity diagnostic method such as biopsy and expand study subjects to low-prevalent population including in the U.S. and Europe in order to minimize the limitations.


The authors declare no conflicts of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

No informed consent.

Author contributions

VJ conceived of the study, searched the literature, assessed the quality of the studies, and drafted the manuscript. SU assessed the quality of the studies, performed the statistical analysis, and drafted the manuscript. AS and SJ participated in the statistical analysis and drafted the manuscript. All authors read and approved the final manuscript.

Author declaration

We wish to draw the attention of the Editor to the following facts which may be considered as potential conflicts of interest and to significant financial contributions to this work. [OR] We wish to confirm that there are no known conflicts of interest associated with this publication and there has been no significant financial support for this work that could have influenced its outcome.

We confirm that the manuscript has been read and approved by all named authors and that there are no other persons who satisfied the criteria for authorship but are not listed. We further confirm that the order of authors listed in the manuscript has been approved by all of us.

We confirm that we have given due consideration to the protection of intellectual property associated with this work and that there are no impediments to publication, including the timing of publication, with respect to intellectual property. In so doing we confirm that we have followed the regulations of our institutions concerning intellectual property.


We thank Matthew Roslund for validation of the search.

Appendix A. Supplementary material

Download file

Supplementary material Supplementary material


Fig. S1

Fig. S1



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a Department of Internal Medicine, University of Hawaii, Honolulu, HI 96813, USA

b Department of Internal Medicine, King Chulalongkorn Memorial Hospital, Bangkok 10330, Thailand

c Department of Internal Medicine, Bassett Medical Center and Columbia University College of Physicians and Surgeons, Cooperstown, NY 13326, USA

d Department of Preventive and Social Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand

Corresponding author at: Department of Internal Medicine, Bassett Medical Center and Columbia University College of Pysicians and Surgeons, Cooperstown, NY 13326, USA.

This study was registered in PROSPERO (registration number: CRD42015029295).

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