Effect of Helicobacter pylori infection on the risk of inflammatory bowel disease: an umbrella review and second-order meta-analysis

Abstract

Background:

Multiple meta-analyses have evaluated the effect of Helicobacter pylori (H. pylori) infection on the risk of inflammatory bowel disease (IBD), but their findings remain inconsistent.

Objectives:

To critically assess the existing meta-analyses regarding the effect of H. pylori infection on the risk of IBD.

Data sources and methods:

We systematically searched four electronic databases and manually screened the reference lists of relevant articles. A Measurement Tool to Assess systematic Reviews 2 (AMSTAR-2), Grade of Recommendation, Assessment, Development, and Evaluation (GRADE), and Graphical Representation of Overlap for OVErviews (GROOVE) tools were used to assess the methodological quality, evidence quality, and the overall overlap of primary studies among the included meta-analyses, respectively. A second-order meta-analysis was performed on primary studies derived from the included meta-analyses with very high overlap to explore the association of H. pylori infection with IBD risk and identify the potential influencing factors. Risk ratios (RRs) were pooled.

Results:

Twelve meta-analyses encompassing 55 primary studies were included. The methodological quality was very low to low. The evidence quality was very low to high. Moderate- to high-quality evidence suggested that H. pylori virulence factors and antibiotic exposure influenced the association of H. pylori infection with IBD. The overall overlap of primary studies among the included meta-analyses was very high. A second-order meta-analysis demonstrated a negative association of H. pylori infection with any type of IBD (RR: 0.60), Crohn’s disease (RR: 0.53), ulcerative colitis (RR: 0.67), and IBD-unclassified (RR: 0.73). Subgroup analyses demonstrated that both IBD subtypes (P_interaction < 0.01), regions (P_interaction < 0.01), and study designs (P_interaction = 0.05) significantly influenced this association. Sensitivity analyses indicated that the results were robust across IBD subtypes and regions, but not across the study designs.

Discussion:

H. pylori infection seems to exhibit a protective effect against the risk of IBD. This association may be influenced by IBD subtypes, regions, H. pylori virulence factors, and antibiotic exposure.

Design:

This is an umbrella review.

Registration:

The protocol was prospectively registered with the PROSPERO database (CRD42024559958).

Keywords

Crohn’s disease inflammatory bowel disease inflammatory bowel disease unclassified ulcerative colitis

Introduction

Helicobacter pylori (H. pylori), a gram-negative bacterium that colonizes the gastric epithelium under highly acidic conditions, was classified as a Group 1 carcinogen by the World Health Organization in 1994.¹ It is typically transmitted in childhood via oral–oral and fecal–oral routes and persists for life, if left untreated.² Despite the global prevalence of H. pylori infection gradually declining, its estimated prevalence remained as high as 43.9% in 2022.^3,4 It is closely associated with various gastrointestinal diseases, including chronic gastritis, peptic ulcer, gastric cancer, and gastric mucosa-associated lymphoid tissue lymphoma.^5–9 Furthermore, emerging evidence suggests a potential association between H. pylori infection and extragastric diseases, such as irritable bowel syndrome,¹⁰ Barrett’s esophagus,¹¹ non-alcoholic fatty liver disease,¹² colorectal polyps/adenomas,¹³ and inflammatory bowel disease (IBD).¹⁴

IBD is a group of chronic, recurrent, non-specific inflammatory diseases of the gastrointestinal tract, comprising Crohn’s disease (CD), ulcerative colitis (UC), and IBD unclassified (IBDU).¹⁵ Its primary clinical manifestations include abdominal pain, diarrhea, bloody stools, and weight loss.¹⁶ In recent years, the global incidence of IBD has been steadily increasing, particularly in developed countries.^17,18 Although the pathogenesis of IBD remains unclear, it is widely considered a multi-factorial disease influenced by genetic susceptibility, environmental factors, immune dysregulation, and gut microbiota dysbiosis.^19–21

Epidemiological studies indicated a significantly lower prevalence of H. pylori infection in patients with IBD compared to non-IBD controls, suggesting that H. pylori infection might play a protective role against IBD.²² As a gastric pathogen, H. pylori may influence the onset and progression of IBD through multiple mechanisms. Specifically, it can modulate the composition and abundance of gut microbiota, restore the balance between T helper 17 and regulatory T cells (Th17/Treg), and promote the polarization of macrophages toward the anti-inflammatory M2 phenotype.^23–26 While several studies, including meta-analyses of observational data, have investigated the effects of H. pylori infection on the development and progression of IBD, the evidence remains inconsistent, partly due to methodological limitations, variability in diagnostic criteria for H. pylori infection, and heterogeneity among studies.^14,27 While prior umbrella reviews have assessed environmental risk factors for IBD, they have rarely explored the potential role of H. pylori infection and never systematically reviewed the existing evidence regarding the effect of H. pylori infection on IBD.^28–30

For this reason, we conducted this umbrella review to assess the methodological quality and evidence quality of existing meta-analyses on the effects of H. pylori infection on IBD risk, and to further investigate their association and potential influencing factors.

Methods

This umbrella review was conducted in accordance with the Preferred Reporting Items for Overviews of Reviews (PRIOR) reporting guidelines³¹ (Supplemental Table 1), and the protocol was prospectively registered with the PROSPERO database (CRD42024559958).

Search strategy

We conducted a comprehensive search across the Cochrane Library, EMBASE, PubMed, and Web of Science databases to identify all systematic reviews and meta-analyses investigating the effects of H. pylori infection on the risk of IBD. The last search was performed on November 5, 2024. In addition, search sensitivity was enhanced by the Medical Subject Heading (MeSH) terms and free-text words. Search items were as follows: (1) “H. pylori”, “Helicobacter pylori”, “Helicobacter nemestrinae”, “Campylobacter pylori”, “Campylobacter pylori subsp. Pylori”; (2) “Inflammatory Bowel Diseases”, “Inflammatory Bowel Disease”, “Bowel Diseases, Inflammatory”, “Crohn Disease”, “Crohn’s Disease”, “Crohns Disease”, “Crohn’s Enteritis”, “Inflammatory Bowel Disease 1”, “Regional Enteritis”, “Ileocolitis”, “Ileitis, Terminal”, “Terminal Ileitis”, “Ileitis, Regional”, “Regional Ileitides”, “Regional Ileitis”, “Enteritis, Granulomatous”, “Granulomatous Enteritis”, “Enteritis, Regional”, “Colitis, Granulomatous”, “Granulomatous Colitis”, “Colitis, Ulcerative”, “Colitis Gravis”, “Idiopathic Proctocolitis”, “Inflammatory Bowel Disease, Ulcerative Colitis Type”, “Ulcerative Colitis”, “Inflammatory bowel disease unclassified”; and (3) “Meta-analysis”, “Overview”, “Systematic review”, “Review, Systematic”, “Umbrella Review”. Two authors (X.W. and H.Z.) independently searched the literature and included eligible articles by screening titles, abstracts, and full texts. Any disagreements were resolved through discussion or consultation with a third author (X.Q.). In addition, the reference lists of eligible articles were manually searched to ensure completeness and avoid omissions.

Eligibility criteria

Meta-analyses would be eligible for inclusion if they investigated the effect of H. pylori infection on the risk of IBD and reported risk ratios (RRs) or odds ratios (ORs) with their 95% confidence intervals (95% CIs). Each meta-analysis included at least two primary studies. Exclusion criteria were as follows: (1) duplicate publications; (2) studies without meta-analyses, including systematic reviews without meta-analysis; (3) meta-analyses where the search strategy was unknown or lacking; and (4) studies that did not explore the effect of H. pylori infection on the risk of IBD.

Data extraction

The following information was extracted: first author, publication year, country, number of primary studies and patients included, design of primary studies included (e.g., case–control, cohort, cross-sectional), research objectives, main findings, outcomes of interest, effects models, effect estimates (e.g., RR, OR, 95% CI), heterogeneity (I²), and publication bias assessment. If a meta-analysis conducted subgroup analyses, the results of the subgroup analyses would be further extracted. Two investigators (X.W. and H.Z.) independently extracted data from the included meta-analyses and resolved any disagreements through discussion or consultation with a third investigator (X.Q.).

Methodological quality of the included meta-analyses

A Measurement Tool to Assess Systematic Reviews 2 (AMSTAR-2) was used to assess the methodological quality of the included meta-analyses.^32,33 This tool comprised 16 items, of which 7 (2, 4, 7, 9, 11, 13, and 15) were identified as critical items for assessing the validity of a review and its conclusions. The responses to the items were categorized as “yes”, “partial yes”, or “no”. The “critical flaw” was defined as any critical item that was lacking, and the “non-critical weakness” was defined as any non-critical item that was lacking. In the overall confidence rating of the included meta-analyses, methodological quality was classified as “high” (no or 1 non-critical weakness), “moderate” (more than 1 non-critical weakness), “low” (1 critical flaw with or without non-critical weaknesses), and “critically low” (more than one critical flaw with or without non-critical weaknesses). Two investigators (X.W. and H.Y.) independently assessed the methodological quality of the meta-analyses included, with any disagreements resolved through discussion or consultation with a third investigator (X.Q.).

Quality of evidence of the included meta-analyses

The Grade of Recommendation, Assessment, Development, and Evaluation (GRADE) system was used to evaluate the quality of evidence derived from meta-analyses.³⁴ This system comprised five downgrading factors (risk of bias, inconsistency, indirectness, imprecision, and publication bias) and three upgrading factors (large magnitude of effect, the effect of plausible confounding, and dose–response gradient). The quality of evidence in the included meta-analyses was classified into four levels: “high”, “moderate”, “low”, and “very low”. The downgrading criteria were as follows: (1) risk of bias was rated as high, or not assessed; (2) I² > 50% without reasonable explanation for heterogeneity, suggesting inconsistency; (3) as for indirectness, the difference was significant between the meta-analysis and the primary study review question; (4) as for imprecision, effect estimates were not statistically significant; and (5) publication bias was deemed serious, or not evaluated. The upgrading criteria were as follows: (1) the magnitude of effect was large with an estimated effect size (OR/RR) of >2.0 or <0.5, or >5.0 or <0.2; (2) all plausible confounding factors were corrected; and (3) the presence of a dose–response gradient. Two investigators independently assessed the quality of evidence in the included meta-analyses (X.W. and H.Y.), with any disagreements resolved through discussion or consultation with a third investigator (X.Q.).

Overlap of primary studies included in meta-analyses

If two or more meta-analyses with the same exposure(s) and outcome(s) included identical primary studies, potential overlap would be considered.³⁵ The Graphical Representation of Overlap for OVErviews (GROOVE) tool was utilized to calculate the Corrected Covered Area (CCA) and evaluate the overlap of primary studies across the included meta-analyses. In the assessment of overall study overlap, CCA was categorized as 0%–5% (slight overlap), 6%–10% (moderate overlap), 11%–15% (high overlap), and above 15% (very high overlap). Two investigators (X.W. and H.Z.) independently evaluated the overlap of included primary studies and resolved any disagreements by consulting a third investigator (X.Q.).

Synthesis of evidence from included meta-analyses

We systematically summarized the characteristics of the included meta-analyses, including the first author, publication year, number of included primary studies and patients, research objectives, main findings, and outcomes of interest. If the overall overlap of primary studies was very high (CCA > 15%), the direct combination of effect sizes may lead to misleading conclusions.^35,36 As previously mentioned, we would extract data from the primary studies included in the meta-analyses, but not directly combine the effect sizes reported in the meta-analyses.³⁷

Risk of bias assessment of primary studies

The Newcastle–Ottawa Scale was used to assess the quality of the included cohort and case–control studies, which covers three domains, including selection, comparability, and outcome (for cohort studies) or exposure (for case–control studies). The comprehensive score of risk of bias was ⩾7 points, 4–6 points, and ⩽3 points, which were determined as high, moderate, and low quality, respectively.

The Joanna Briggs Institute Critical Appraisal Checklist for Analytical Cross-Sectional Studies was used to assess the quality of the included cross-sectional studies, which covers eight domains. Each item was answered as “Yes”, “No”, “Unclear”, or “Not applicable”.³⁸ The studies were categorized as high (⩾70% “Yes”), moderate (50%–69% “Yes”), and low quality (<50% “Yes”).

Statistical analyses

All analyses were conducted using RStudio version 4.4.2 (R Foundation for Statistical Computing, Vienna, Austria) and Review Manager version 5.4 (Cochrane Collaboration, Oxford, UK). The ORs and RRs with their 95% CIs were pooled using a random-effects model. Statistical heterogeneity was assessed via I² statistics, and I² > 50% was considered statistically significant heterogeneity. Subgroup and meta-regression analyses were conducted to identify potential sources of heterogeneity. The following covariates were used in the subgroup analyses: IBD subtype (CD vs UC vs IBDU), mean age (⩽16 vs >16), region (Asia vs Europe vs America vs Oceania), type of country (developed vs developing), diagnostic methods of H. pylori (histology vs serology vs urea breath test (UBT) vs polymerase chain reaction (PCR) vs immunohistochemistry (IHC) vs rapid urease test (RUT) vs multiple methods), and study design (case–control vs cohort vs cross-sectional). Subgroup analyses were used to explore the potential influence of several confounders. The interaction between subgroups was tested, and p < 0.1 was considered to indicate a notable confounder. If the subgroup analyses identified notable confounders with a P_interaction < 0.1, sensitivity analyses would be further performed by removing studies one by one.

Results

Umbrella review

Study selection

The initial search identified 370 records. After removing 99 duplicates, 271 studies were screened based on their titles and abstracts, resulting in 16 potentially eligible studies (Figure 1). Ultimately, 12 meta-analyses were included in this umbrella review after screening the full texts.^{14,22,27,39–47} The detailed list of excluded records is provided in Supplemental Table 3.

Figure 1.

Flow chart of study selection.

Characteristics and outcomes of the included meta-analyses

Among the included meta-analyses, two focused on CD alone^{14,22,27,39–47} (Table 1). Among these meta-analyses, 11 conducted subgroup analyses to investigate the source of heterogeneity, while one did not²⁷ (Supplemental Table 4). They were published between 2010 and 2023. The number of primary studies ranged from 3 to 58. Ten out of 12 meta-analyses employed a random-effects model, while the remaining 2 utilized a fixed-effect model.^39,44

Table 1.

Characteristics of included meta-analyses.

Study	Type of IBD	No. of studies	No. of cases/total	Study design	Effects model	Publication bias assessment	OR/RR (95% CIs)	p-Value	I²(%)	AMSTAR-2	GRADE
Kong et al.³⁹	IBD	6	356/2236	Case–control (4), Cohort (2)	Fixed	NA	0.62 (0.34, 1.12)	0.12	36.00	Critically low	Very low
Bouriat et al.²⁷	IBD	19	2477/5433	Case–control (19)	Random	Begg funnel plots	0.42 (0.32, 0.56)	<0.0001	69.00	Critically low	Very low
Shirzad-Aski et al.²²	IBD	58	13,549/520,103	Case–control (32), Cohort (23), Cross-sectional (3)	Random	Begg funnel plots and Egger’s test	0.45 (0.39, 0.52)	<0.001	79.00	Low	Moderate
Zhong et al.⁴⁰	IBD	13	5680/284,045	Case–control (13)	Random	NA	0.44 (0.34, 0.59)	0.000	80.10	Critically low	Very low
Imawana et al.⁴¹	IBD	32	4607/9273	Case–control (22), Cohort (11)	Random	Begg funnel plots and Egger’s test	0.58 (0.49, 0.68)	0.000	77.00	Critically low	Low
Wang et al.⁴²	CD	20	2055/5497	Case–control (20)	Random	Begg funnel plots	0.41 (0.32, 0.53)	<1 × 10⁻⁵	64.00	Critically low	Very low
Tepler et al.⁴³	IBD	3	960/1748	Case–control (2), Cross-sectional (1)	Random	Begg funnel plots and Egger’s test	0.31 (0.22, 0.44)	<1 × 10⁻⁵	0.00	Critically low	High
Castaño-Rodríguez et al.¹⁴	IBD	40	6130/80,789	Case–control (40)	Random	Egger’s test	0.43 (0.36, 0.50)	<1 × 10⁻¹⁰	61.81	Critically low	Moderate
Wu et al.⁴⁴	IBD	10	1299/3116	Case–control (10)	Fixed	Begg funnel plots and Egger’s test	0.48 (0.43, 0.54)	<1 × 10⁻⁵	21.00	Critically low	Moderate
Rokkas et al.⁴⁵	IBD	33	4190/9163	Case–control (6), Cohort (26), Cross-sectional (1)	Random	Begg funnel plots and Egger’s test	0.62 (0.55, 0.71)	<0.001	77.00	Critically low	Very low
Cui et al.⁴⁶	CD	13	938/66,856	Case–control (13)	Random	Egger’s test	0.54 (0.42, 0.70)	<1 × 10⁻⁵	64.00	Critically low	Very low
Luther et al.⁴⁷	IBD	23	2930/5874	Case–control (23)	Random	Begg funnel plots and Egger’s test	0.64 (0.54, 0.75)	NA	75.80	Critically low	Very low

95% CIs, 95% confidence intervals; AMSTAR-2, Assessment of Multiple Systematic Reviews-2; CD, Crohn’s disease; GRADE, Grade of Recommendation, Assessment, Development, and Evaluation; IBD, inflammatory bowel disease; NA, not applicable; τ², Tau-squared.

Eleven meta-analyses reported a negative association between H. pylori infection and IBD^{14,22,27,40–47} (Table 1), but the remaining one, which focused on the pediatric population, found no significant association.³⁹ The overall overlap of primary studies among the included meta-analyses was very high (CCA = 22.85%; Supplemental Figure 1(A)).

Methodological quality of the included meta-analyses

The meta-analyses included in this umbrella review did not fully meet all 7 critical items of the AMSTAR-2 checklist (Supplemental Table 5). Among these meta-analyses, 1 (8.33%) was rated as low quality,²² and 11 (91.67%) as critically low quality.^{14,27,39–47} This was mainly attributed to the lack of a pre-registered or published protocol^{14,27,39–47} (Q2, n = 11) and the failure to provide a list of excluded studies^{14,22,27,39–47} (Q7, n = 12). When the quality assessment criteria for the protocol and the list of excluded studies were ruled out, 1 study (8.33%) was rated as high quality,⁴³ and 1 (8.33%) as moderate quality.²²

The quality evidence of the included meta-analyses

In total, 67 pieces of evidence derived from 12 meta-analyses were assessed. Specifically, the evidence levels for 4, 9, 10, and 44 pieces of evidence were rated as high, moderate, low, and very low, respectively (Supplemental Table 6). As for the downgrading criteria, 22 pieces of evidence from 6 meta-analyses indicated a risk of bias;^{27,40,42,44,45,47} 49 pieces of evidence from 9 meta-analyses demonstrated inconsistency;^{14,22,27,40–42,45–47} no meta-analysis was affected by indirectness; 13 pieces of evidence from 3 meta-analyses demonstrated imprecision;^22,39,43 and 4 pieces of evidence from 4 meta-analyses showed publication bias.^27,42,46,47 As for the upgrading criteria, 35 pieces of evidence from 10 meta-analyses demonstrated a large magnitude of effect;^{14,22,27,40–46} 30 pieces of evidence from 12 meta-analyses indicated that confounding factors did not reduce the effect;^{14,22,27,39–47} and no meta-analysis showed evidence of a dose–response gradient. In addition, 2 high-quality studies specified the associations, of which 1 focused on the association of H. pylori infection with IBDU and another on the association of cytotoxin-associated gene A positive (cagA+) strains of H. pylori infection with IBD.

IBD subtype

Nine meta-analyses investigated the association between H. pylori infection and different subtypes of IBD^{14,22,39–41,43–45,47} (Figure 2).

Figure 2.

Forest plots of effect estimates of IBD subtype.

CD: Eight meta-analyses suggested a negative association between H. pylori infection and CD,^{14,22,40,41,43–45,47} with 1 rated as “High” quality of evidence,⁴³ 2 as “Moderate,”^14,22 and 5 as “Very low” according to the GRADE assessment.^{40,41,44,45,47} However, 1 meta-analysis focusing on pediatric populations found no significant association, with a very low quality of evidence.³⁹ The overall overlap of primary studies investigating the association of H. pylori infection with CD among the included meta-analyses was very high (CCA = 26.49%; Supplemental Figure 1(B)).

UC: Seven meta-analyses suggested a negative association between H. pylori infection and UC,^{14,22,39–41,43–45,47} with 2 rated as “Low”^14,22 and 5 as “Very low” according to the GRADE.^{40,41,44,45,47} However, 2 meta-analyses found no significant association, with a very low quality of evidence.^39,43 The overall overlap of primary studies investigating the association ofH. pylori infection with UC among the included meta-analyses was very high (CCA = 20.00%; Supplemental Figure 1(C)).

IBDU: Two meta-analyses suggested a negative association between H. pylori infection and IBDU, with 1 rated as “High”¹⁴ and the other as “Moderate”²² according to the GRADE. The overall overlap of primary studies investigating the association of H. pylori infection with IBDU among the included meta-analyses was very high (CCA = 20.00%; Supplemental Figure 1(D)).

Mean age

Two meta-analyses suggested a negative association between H. pylori infection and IBD across different age groups^14,22 (Figure 3(a)). One suggested a more significant negative association in patients aged ⩽16 years¹⁴ (pooled RR: 0.24, 95% CI: 0.14–0.43, I² = 22.87%, GRADE rating: Moderate). Another meta-analysis found no significant difference between the <42 and >42 years groups²² (GRADE rating: Very low).

Figure 3.

Forest plots of effect estimates. (a) Mean age. (b) Region. (c) Type of country.

Region

Three meta-analyses suggested a negative association between H. pylori infection and IBD across different geographic regions (GRADE rating: Very low to Low)^14,22,41 (Figure 3(b)).

Type of country

One meta-analysis suggested a negative association between H. pylori infection and IBD across different levels of economic development⁴² (GRADE rating: Very low; Figure 3(c)).

Diagnostic methods of H. pylori

Five meta-analyses suggested a negative association between H. pylori infection and IBD across different H. pylori diagnostic methods^{14,22,45–47} (GRADE rating: Very low to Low; Figure 4(a)).

Figure 4.

Forest plots of effect estimates. (a) Diagnostic methods of Helicobacter pylori. (b) Study design.

Study design

One meta-analysis suggested a negative association between H. pylori infection and IBD across different study designs⁴⁵ (GRADE rating: Very low; Figure 4(b)).

Second-order meta-analysis

Characteristics of primary studies included in meta-analysis

A total of 76 primary studies were recruited in the included meta-analyses and published between 1994 and 2019. However, 22 primary studies were excluded from the second-order meta-analysis due to the following reasons: abstracts, letters, and studies that lack data on the association of H. pylori infection with IBD risk (Supplemental Table 7). Finally, our second-order meta-analysis was performed based on the remaining 55 primary studies, including the 2 distinct cohorts (Hong Kong and Hungary) reported in the study by Farkas et al.⁴⁸ (Supplemental Table 8). These primary studies were distributed across Asia (n = 17, 30.91%), Europe (n = 29, 52.73%), America (n = 8, 14.55%), and Oceania (n = 1, 1.81%). They comprised 12 cohort studies, 37 case–control studies, and 6 cross-sectional studies.

Results of second-order meta-analysis

A second-order meta-analysis of 55 primary studies (n = 414,673) involving major IBD subtypes (including CD, UC, and IBDU) confirmed a negative association between H. pylori infection and IBD (pooled RR: 0.60, 95% CI: 0.55–0.66, I² = 64.00%; Figure 5). Of these, 28 (50.90%) were rated as high quality and 27 (49.10%) as moderate quality (Supplemental Tables 9–11).

Figure 5.

Forest plots of effect estimates in the second-order meta-analysis.

IBD subtype

Subgroup analysis based on IBD subtype demonstrated consistent negative associations with H. pylori infection: CD (pooled RR: 0.53, 95% CI: 0.46–0.60, I² = 64.00%, n = 47), UC (pooled RR: 0.67, 95% CI: 0.60–0.75, I² = 61.00%, n = 45), and IBDU (pooled RR: 0.73, 95% CI: 0.58–0.92, I² = 0.00%, n = 10). The interaction was statistically significant among all subgroups (P_interaction < 0.01; Figure 5).

Mean age

Subgroup analysis based on mean age categorized 55 primary studies into pediatric (⩽16 years old, n = 6) and adult (>16 years old, n = 47) groups. Both groups exhibited a negative association between H. pylori infection and IBD: pediatric (pooled RR: 0.55, 95% CI: 0.38–0.79, I² = 62.00%) and adult (pooled RR: 0.59, 95% CI: 0.54–0.65, I² = 62.00%). The interaction was not statistically significant among all subgroups (P_interaction = 0.42; Figure 5).

Region

Subgroup analysis based on region categorized 55 primary studies into 4 groups: Asia (n = 17), Europe (n = 29), America (n = 8), and Oceania (n = 1). The majority of these groups exhibited a negative association between H. pylori infection and IBD: Asia (pooled RR: 0.50, 95% CI: 0.45–0.54, I² = 7.00%), Europe (pooled RR: 0.65, 95% CI: 0.57–0.74, I² = 62.00%), and America (pooled RR: 0.70, 95% CI: 0.58–0.85, I² = 61.00%). By contrast, no significant association was observed in the Oceania group (pooled RR: 1.69, 95% CI: 0.81–3.51). The interaction was statistically significant among all subgroups (P_interaction < 0.01; Figure 5).

Type of country

Subgroup analysis based on country development status categorized 55 primary studies into developed country (n = 40) and developing country (n = 15) groups. Both groups exhibited a negative association between H. pylori infection and IBD: developed country (pooled RR: 0.63, 95% CI: 0.56–0.70, I² = 65.00%) and developing country (pooled RR: 0.56, 95% CI: 0.48–0.64, I² = 60.00%). The interaction was not statistically significant among all subgroups (P_interaction = 0.21; Figure 5).

Diagnostic methods of H. pylori

Subgroup analysis based on different diagnostic methods categorized 55 primary studies into 7 groups: histology (n = 8), serology (n = 17), UBT (n = 12), PCR (n = 6), IHC (n = 3), RUT (n = 1), and multiple methods (n = 8). All groups exhibited a negative association: histology (pooled RR: 0.58, 95% CI: 0.48–0.71, I² = 36.00%), serology (pooled RR: 0.60, 95% CI: 0.52–0.69, I² = 65.00%), UBT (pooled RR: 0.54, 95% CI: 0.41–0.70, I² = 77.00%), PCR (pooled RR: 0.77, 95% CI: 0.54–1.11, I² = 33.00%), IHC (pooled RR: 0.64, 95% CI: 0.47–0.67, I² = 47.00%), RUT (pooled RR: 0.48, 95% CI: 0.34–0.67), and multiple methods (pooled RR: 0.68, 95% CI: 0.51–0.91, I² = 75.00%). The interaction was not statistically significant among all subgroups (P_interaction = 0.51; Figure 5).

Study design

Subgroup analysis based on study design categorized 55 primary studies into case–control study (n = 37), cohort study (n = 12), and cross-sectional study (n = 6) groups. All groups exhibited a negative association: case–control study (pooled RR: 0.56, 95% CI: 0.50–0.62, I² = 65.00%), cohort study (pooled RR: 0.66, 95% CI: 0.55–0.78, I² = 56.00%), and cross-sectional study (pooled RR: 0.79, 95% CI: 0.59–1.05, I² = 66.00%). The interaction was statistically significant among all subgroups (P_interaction = 0.05; Figure 5).

Meta-regression analysis

Meta-regression analysis confirmed that study design (case–control vs non case–control) was a significant source of heterogeneity (p = 0.037). By contrast, other variables, such as mean age, region, type of country, and diagnostic methods of H. pylori, did not significantly contribute to heterogeneity (p > 0.05; Supplemental Table 12).

Sensitivity analysis

Further sensitivity analyses were performed for subgroups based on IBD subtypes, regions, and study designs, which were identified as notable confounders of heterogeneity. Across IBD subtypes and regions, the heterogeneity was not significantly influenced by leaving out any individual primary study (Supplemental Tables 13 and 14). Across study designs, the heterogeneity might be attributed to the studies by Pronai et al.⁴⁸ and Sonnenberg et al.⁴⁹ (Supplemental Table 15).

Discussion

Current evidence from meta-analyses revealed inconsistencies regarding the effect of H. pylori infection on the development or progression of IBD. Specifically, very low-quality evidence suggested no significant association, but low- to high-quality evidence suggested a negative association. After synthesizing the overall evidence, H. pylori infection might serve as a protective factor against IBD.

There was a very high overlap (CCA = 22.85%) among the primary studies included in the meta-analyses, which might affect the robustness of the findings. To address these limitations, this umbrella review performed a second-order meta-analysis to adjust for significant overlap and conducted stratified analyses to evaluate the impact of confounding factors. We integrated data from 55 primary studies among 12 meta-analyses involving various IBD subtypes, revealing a protective effect of H. pylori infection against the development and progression of IBD, with a more significant protective effect observed in CD. Notably, region, virulence factors of H. pylori, and antibiotic exposure could influence this association. By contrast, other potential confounding factors, such as study design, mean age, type of country, and diagnostic methods of H. pylori, did not significantly influence this association.

Based on the AMSTAR-2 assessment, all included meta-analyses were found to have critical items limitations in their methodology, particularly the lack of a pre-registered protocol and a comprehensive list of excluded studies. According to the GRADE assessment, 80.60% of the evidence was classified as very low to low quality, primarily due to inconsistency (I² > 50%) leading to a downgrade in the quality of evidence.

H. pylori may play a protective role against IBD through multiple mechanisms. First, H. pylori infection can modulate the composition and abundance of the gut microbiota, thereby influencing the pathogenesis and progression of IBD.⁵¹ It can reduce the abundance of Bacteroidetes, increase the abundance of Firmicutes, and promote the production of short-chain fatty acids.⁵² Second, H. pylori infection alleviates inflammation in IBD patients by activating tissue-repair mechanisms and modulating both the host innate and adaptive immune responses.²⁴ Specifically, it promotes the polarization of macrophages toward an anti-inflammatory M2 macrophages. The cagA gene of H. pylori induces the upregulation of Treg cells, leading to increased production of anti-inflammatory cytokines, such as IL-10, IL-13, and TGF-β. H. pylori also promotes the generation of tolerogenic dendritic cells (DCs), which activate the NLRP3 inflammasome to induce epithelial IL-18 secretion, thereby inhibiting Th17 cell differentiation and enhancing Treg activity.^25,53,54 This interaction forms a negative feedback loop between Treg cells and DCs. Third, other components of H. pylori, such as flagella, bacterial urease enzyme, and superoxide dismutase, may also inhibit the production of pro-inflammatory cytokines.⁵⁵

Among the different subtypes of IBD, CD is primarily associated with a Th1-mediated immune response, while UC is predominantly linked to a Th2-mediated immune response.^22,56–59 H. pylori infection primarily induced the host immune response skewed toward a Th1 phenotype, which may provide stronger protection against CD.^60–62 Furthermore, most current evidence on this association comes from case–control studies comparing the prevalence of H. pylori infection between IBD patients and non-IBD controls.^48,63 However, this study design is susceptible to biases, such as recall bias, selection bias, and residual confounding, which may exaggerate the observed protective effect.⁶⁴

Our stratified analyses indicated that the region significantly influences the observed protective effect, and low-quality evidence suggested that the protective effect might be more significant in Eastern populations.¹⁴ This geographic variation could primarily result from the differential distribution of cagA+ H. pylori strains. Specifically, cagA+ strains were predominant in East Asia (approaching 100%), while their prevalence was significantly lower in Western populations (60%–70%).⁶⁵ Tepler et al.⁴³ reported a significant reduction in IBD incidence, associated with CagA seropositive H. pylori strains, but not with CagA seronegative strains. Infection with high-virulence type I strains (cagA+/vacA−) was inversely correlated with disease severity and extraintestinal manifestations in IBD, while low-virulence type II strains (cagA−/vacA+) showed weaker associations.⁶⁶ A recent Mendelian randomization study further implicated cagA as a causal protective factor for IBD, whereas vacA exhibited no significant association.⁶⁷ Collectively, these findings suggested that the cagA gene might serve as a potential mediator of the protective effects of H. pylori, but further mechanistic validation is essential to confirm this role.

Our stratified analyses also indicated that potential confounding factors, including study design, mean age, type of country, and diagnostic methods of H. pylori, did not significantly influence the observed protective effect. However, Kong et al.³⁹ found no significant associations in the pediatric populations. But their study was limited by a small sample size, critically low methodological quality, and very low-quality evidence, thereby undermining the reliability of their findings.

The protective effect of H. pylori infection in IBD patients may be influenced by prior antibiotic exposure or commonly prescribed medications.⁶⁸ Moderate-quality evidence suggested that antibiotic exposure may enhance this protective effect.¹⁴ However, this association was confounded by bias from medical indication, as antibiotics can eradicate H. pylori, reducing its prevalence in IBD populations. Antibiotic exposure was associated with an increased risk of new-onset IBD in a positive nonlinear dose–response association, with a higher association observed in individuals aged ⩾40 years.^69,70 In addition, antibiotics targeting gastrointestinal pathogens demonstrated a stronger effect, which could be attributed to the gut dysbiosis and fungal overgrowth.⁷¹ However, commonly prescribed medication for IBD patients, such as 5-aminosalicylic acid drugs and corticosteroids, showed no significant impact on this protective effect.¹⁴

H. pylori infection, a well-established major etiology in various gastrointestinal diseases, especially gastric cancer, warrants eradication therapy as recommended by international guidelines.^72,73 However, current guidelines did not clarify whether H. pylori should be eradicated in patients with IBD. The incidence of IBD significantly increased 3 years after H. pylori eradication, particularly among patients aged ⩾30 years.⁷⁴ Proposed mechanisms for this finding involve two key aspects of standard eradication regimens. First, eradication therapy typically employs broad-spectrum antibiotics (e.g., amoxicillin, clarithromycin, tetracyclines), which inevitably induce gut dysbiosis through non-selective microbial suppression.^75–77 Second, the use of proton pump inhibitors can significantly increase the risk of enteric infections in IBD patients.⁷⁸ Collectively, these medications may disrupt intestinal homeostasis, potentially outweighing the benefits of H. pylori eradication in IBD patients.

Our study had several notable strengths. First, to our knowledge, this was the first specific umbrella review synthesizing evidence from meta-analyses to evaluate the effects of H. pylori infection on the development and progression of IBD. Second, we addressed the critical issue of primary studies’ overlap in meta-analyses by performing a second-order meta-analytic approach, which significantly enhanced the precision of pooled estimates. Third, our stratified analyses identified key confounding factors that may influence the protective effects of H. pylori, providing feasible insights for future research. Nevertheless, several limitations should be acknowledged. First, we only included studies with meta-analyses, which might introduce selection bias. Second, as an umbrella review inherently constrained by the temporal scope of the included meta-analyses, the primary studies were published before 2019. However, the methodological design enhanced the robustness of the findings. Third, the majority of the primary studies did not report detailed information on antibiotic use, social status, hygiene, and childhood environment, which compromised further subgroup analyses according to these confounders.

Conclusion

Through a systematic evaluation of methodological quality and evidence quality among existing meta-analyses, this umbrella review confirms that H. pylori infection has a protective effect against the risk of IBD. Certainly, high-quality and large-scale prospective studies should further confirm the temporal causality between H. pylori infection and IBD. Meanwhile, systematic reviews and meta-analyses should be more strictly performed to enhance the validity of evidence synthesis. In the future, it is also essential to investigate the risk of IBD by comparing endoscopic findings before and after H. pylori eradication therapy.

Supplemental Material

sj-docx-1-tag-10.1177_17562848261444293 – Supplemental material for Effect of Helicobacter pylori infection on the risk of inflammatory bowel disease: an umbrella review and second-order meta-analysis

Supplemental material, sj-docx-1-tag-10.1177_17562848261444293 for Effect of Helicobacter pylori infection on the risk of inflammatory bowel disease: an umbrella review and second-order meta-analysis by Xiaomin Wang, Haonan Zhao, Honglu Yu, Juan Liu, Yongguo Zhang, Jiang Chen and Xingshun Qi in Therapeutic Advances in Gastroenterology

Footnotes

Acknowledgements

The abstract was partly accepted for presentation as an electronic poster at the Congress of Gastroenterology China (CGC) 2025 Conference.

Declarations

ORCID iD

Xingshun Qi

Supplemental material

Supplemental material for this article is available online.

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