Association of Helicobacter pylori Infection with the Risk of Metabolic Syndrome and Insulin Resistance: An Updated Systematic Review and Meta-Analysis

doi:10.21203/rs.3.rs-789572/v1

Background

Conflicting results of recent studies on the association between Helicobacter pylori (H. pylori) infection and the risk of insulin resistance and metabolic syndrome explored the need for updated meta-analysis on this issue. Therefore, this systematic review aimed to estimate the pooled effect of H. pylori infection on the risk of insulin resistance and metabolic syndrome.

Methods

To identify case-control studies and cohort studies evaluating the association of H. pylori infection with insulin resistance and metabolic syndrome, a comprehensive literature search was performed from international databases including Medline (PubMed), Web of Sciences, Scopus, EMBASE, and CINHAL from January 1990 until January 2021. We used odds ratio with its 95% confidence interval (95%CI) to quantify the effect of case-control studies and risk ratio with its 95%CI for the effect of cohort studies.

Results

22 studies with 206911 participants were included for meta-analysis. The pooled estimate of odds ratio between H. pylori infection and metabolic syndrome in case-control studies was 1.19 (95%CI: 1.05, 1.35; I² = 0%), and in cohort studies, the pooled risk ratio was 1.31 (95%CI: 1.13, 1.51; I² = 0%). Besides, case-control studies showed the pooled odds ratio of 1.54 (95%CI: 1.19, 1.98; I² = 6.88%) for the association between H. pylori infection and insulin resistance.

Conclusion

A positive association was found between H. pylori infection and insulin resistance as well as metabolic syndrome, so planning to eliminate or eradicate H. pylori infection could be an effective solution to improve metabolic syndrome or insulin resistance, and vice versa.

Endocrinology & Metabolism

Internal Medicine

Helicobacter pylori

insulin resistance

metabolic syndrome

systematic review

meta-analysis

Helicobacter pylori (H. pylori) is a gram-negative bacterium and a very common pathogen, which has infected more than half of the world's population. To diagnose this infection, both invasive tests such as upper gastrointestinal endoscopy with gastric biopsy and non-invasive tests such as the urea respiration test, stool test, and blood test are available in clinical practice.[1–3] Although the incidence of H. pylori infection is declining worldwide, the infection is still a communicable disease with serious health consequences. There are many differences in the distribution of H. pylori infection in the population between developed and developing countries. In this instance, almost 80% of infected population in developing countries such as India and Vietnam are before the age of 20 while in developed countries such as the United States and France, the rate of infection peaks between the ages of 20 and 30.[4–8] The prevalence of H. pylori in developing countries is between 85% and 95% while in developed countries, it ranged from 30–50%. Besides, after 2000, the prevalence of H. pylori infection was lower in European countries than before. However, this prevalence in Asian countries remained almost the same.[9, 10] H. pylori infection has different effects on human health, including both gastric and extra-gastric problems. Induced-gastric diseases include gastritis, peptic ulcer disease, functional dyspepsia, reflux disease, and gastric cancer. Extra-gastric complications of H. pylori infection include cardiopulmonary diseases (coronary artery disease and asthma), hematologic diseases (iron deficiency anemia and immune thrombocytopenic purpura), neurologic diseases (ischemic stroke, Parkinson, Alzheimer, and migraines), dermatologic diseases (chronic spontaneous urticaria), and metabolic diseases (metabolic syndrome and insulin resistance).[11–13]

Metabolic syndrome is a complex disorder defined by a combination of risk factors that increase the risk of atherosclerotic cardiovascular disease and type II diabetes.[11] So far, different criteria collections with different numbers of parameters were developed to identify metabolic syndrome, such as National Cholesterol Education Program Adult Treatment Panel III (NCEP ATPIII), World Health Organization (WHO), European Group for the study of Insulin Resistance (EGIR), American Association of Clinical Endocrinology (AACE), and American Heart Association/National Heart, Lung, and Blood Institute (AHA / NHLBI). Among all risk factors defined in different score systems, insulin resistance or impaired glucose tolerance is one of the major components for the diagnosis of metabolic syndrome.[14–17] The role of H. pylori infection on the risk of metabolic syndrome and insulin resistance has been investigated in several studies, but the results of different studies are contradictory. In this instance, several studies have shown a positive association between H. pylori and insulin resistance as well as metabolic syndrome [18–21] while other studies have shown no significant association between H. pylori and these consequences[22, 23]. The occurrence of insulin resistance or metabolic syndrome, which can help prevent and treat these medical conditions more effectively. Thus, the aim of the present study was to determine the pooled effect of the association between H. pylori infection and the risk of metabolic syndrome and insulin resistance using a combination of results of cohorts as well as case-control studies.

This systematic review and meta-analysis was based on the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) which is dedicated to the systematic review and meta-analysis of observational studies.

Search Terms and Complex Search Syntax

All original articles published from January 1990 to January 2021 were searched in international databases including Medline (PubMed), Web of Sciences, Scopus, EMBASE, and CINHAL without language restrictions. The search strategy was performed based on three root keywords of Helicobacter pylori, insulin resistance, and metabolic syndrome and their mesh terms including Campylobacter pylori, Helicobacter, Helicobacter nemestrinae, Campylobacter pylori subsp. pylori, Campylobacter pyloridis, insulin sensitivity, metabolic syndrome X, dysmetabolic syndrome X, metabolic cardiovascular syndrome, and cardiometabolic syndrome. Gray literature was then used to access unpublished articles, dissertations, and international reports. In addition, after the final selection of articles, a manual search was performed by reviewing the references of related articles. The search strategy in international databases was independently conducted by two researchers (MA and AM) and the disputes were resolved by a third person (YM).

Eligibility Criteria

In this research, a meta-analysis of studies aimed at determining the association of H. pylori infection with the occurrence of insulin resistance or metabolic syndrome was considered; meaning that exposure in these studies was the infection of H. pylori and the main outcome was the occurrence of insulin resistance or metabolic syndrome. Therefore, case-control and cohort studies were included in this meta-analysis. The statistical population studied in these initial studies was all individuals, whether they had a specific disease or they were healthy. There were no specific limitations in this research for the method of diagnosing H. pylori infection for inclusion of studies and it was decided that the results would be analyzed based on the diagnostic method of H. pylori. The definition of metabolic syndrome in this study was also based on its international definition, i.e. people who have risk factors such as obesity or overweight, inactivity, insulin resistance, and genetic history of metabolic syndrome.[24, 25] Other studies including cross-sectional studies, case reports, case series, systematic reviews, meta-analyses, letters, and editorials were excluded.

Data Extraction

To extract information, first, a checklist including the first author's name, date of publication, country, type of study, sample size, type of diabetes, bacterial detection method, age (mean and its dispersion), gender (number of male), and effect size (odds ratio or risk ratio) was designed. Then, two authors (MA and AM) independently extracted the data based on the checklist, and the conflicts were resolved by a third person (YM).

Quality Assessment

In this study, to evaluate the quality of included articles, the Joanna Briggs Institute (JBI) critical appraisal checklist was used for case-control studies and cohorts. The purpose of these appraisals is to assess the methodological quality of a study and to determine the extent to which a study has addressed the possibility of bias in its design, conduct, and analysis. JBI critical appraisal tools have been developed by the JBI and collaborators and approved by the JBI Scientific Committee following extensive peer review. The checklist for case-control studies consisted of ten questions and that for the cohort studies were composed of eleven questions related to their methodology, which have been defined in the categories of ‘Yes’, ‘No’, ‘Not Applicable’, and ‘Unclear’. Finally, these studies were scored based on the number of Yes cases.[26, 27]

Statistical Analysis

The effect sizes in this meta-analysis included the odds ratio in case-control studies and the risk ratio in cohort studies. To perform a meta-analysis, first, the logarithm and logarithm error of each of these indicators were estimated, then the results were combined using the random effect model and the pooled estimate of each of these indicators was calculated with a 95% confidence interval (95%CI). Eggers test and funnel plot asymmetry were used to examine and determine the potential publication bias. In this study, the Cochran Q test and I² statistics were used to assess statistical heterogeneity between studies. According to the Cochrane criteria and I² index, the rate of heterogeneity was divided into 4 categories: 0% to 40% (may not be important), 30% to 60% (may represent moderate heterogeneity), 50% to 90% (may represent substantial heterogeneity), and finally 75% and above (considerable heterogeneity).[28-31] Sensitivity analysis was performed to determine the overall effect without considering any of the initial studies. All statistical analyses were performed using STATA 16.0 (Stata Corp., College Station, TX, USA).

Study Characteristics

After completing the search in international databases, 782 studies were retrieved. After removal of duplicates, screening by titles, abstracts, and full texts was performed considering inclusion and exclusion criteria; 22 studies remained to meta-analyze the association between H. pylori infection and insulin resistance and metabolic syndrome (Figure 1). The characteristics of the studies included in this meta-analysis were reported in Table 1.

For this meta-analysis, 18 case-control studies[32-49] were included, of which 9 studies [32, 34, 38, 39, 41, 42, 46, 48, 49] determined the association of H. pylori infection with the occurrence of metabolic syndrome and 9 studies[33, 35, 36, 40, 43-45, 47] determined the association of H. pylori infection with the occurrence of insulin resistance in patients with diabetes. Besides, 4 cohort studies[19, 50-52] were analyzed, of which 2 studies[50, 52] examined the presence of H. pylori infection in connection with metabolic syndrome and 2 studies[19, 51] on insulin resistance (Table 1).

Association of H. pylori infection with metabolic syndrome (a combination of case-control studies)

9 case-control studies were evaluated the association of H. pylori infection with the occurrence of metabolic syndrome. After combining the results of these case-control studies, the pooled estimate of odds ratio was 1.19 with a 95% confidence interval of 1.05 to 1.35. The rate of heterogeneity was significantly lower and equal to zero percent with a significant level of 0.98 (Figure 2a).

The Eggers test and funnel plot showed that the publication bias did not occur (B = 0.54; SE = 0.40; P-value = 0.181) (Figure 2b). Besides, sensitivity analysis showed that if each study was omitted, the pooled odds ratio and its 95% confidence interval would be in line with the overall estimates, except for the study by Refeali et al.[46], which, if omitted, increased the pooled odds ratio to 1.29 with wider 95% confidence interval of 1.02 to 1.64 (Figure 2c).

In Table 2, subgroup analysis was performed based on the diagnostic method of H. pylori. The results showed that regarding the diagnostic method of anti-H. pylori antibody, the pooled odds ratio was 1.26 (95%CI: 1.01, 1.70) and according to the C urea breath test (UBT), it was 1.17 (95%CI: 1.02, 1.35; p value: 0.910).

Association of H. pylori infection with insulin resistance (a combination of case-control studies)

10 case-control studies evaluated the association between H. pylori infection and the occurrence of insulin resistance in diabetic patients. After combining the results of these case-control studies, the pooled odds ratio was 1.54 with a 95% confidence interval of 1.19 to 1.98. (Figure 3a).

The results of the Eggers test and funnel plot showed no publication bias (B = -0.17; SE = 0.61; P-value = 0.791) (Figure 3b). In addition, the sensitivity analysis showed that if any of the studies were omitted, the pooled odds ratio would be in line with the overall pooled odds ratio result. Only if the study of Allam et al. [44]were removed, the pooled odds ratio would be equal to 1.70 with a 95% confidence interval of 1.33 to 2.16 (Figure 3c).

In Table 2, subgroup analysis was performed based on the diagnostic method of H. pylori, types of diabetes, gender of population, and continent. The results showed that regarding the diagnostic method of anti-H. pylori antibody, the pooled odds ratio for the occurrence of insulin resistance in diabetic patients with H. pylori infection was equal to 1.63 (95%CI: 1.25, 2.12) and according to the diagnostic method of the rapid urease test (RUT) & histology, it was equal to 1.33 (95%CI: 0.56, 3.16; p value: 0.661). Subgroup analysis based on the type of diabetes showed that the incidence chance of insulin resistance in diabetes mellitus patients with H. pylori infection was 1.19 (95%CI: 1.00, 1.78), and in type II diabetic patients with H. pylori infection, it was 1.80 (95%CI: 1.34, 2.42; p value: 0.192). The subgroup analysis based on the continent of study showed the odds ratio of the presence of H. pylori infection and the occurrence of insulin resistance in Asian population was 1.67 (95%CI: 1.23, 2.26), and the corresponding estimates in America and Africa were 1.47 (95%CI: 0.89, 2.44) and 1.00 (95%CI: 0.26, 3.77; p value: 0.63), respectively.

Association of H. pylori infection with insulin resistance and metabolic syndrome (a combination of cohort studies)

Finally, cohort studies were evaluated. Two cohort studies determined the association between H. pylori infection and the incidence of insulin resistance; in the study by Hsieh et al.[51], the risk ratio of H. pylori infection and insulin resistance was 1.30 (95%CI: 1.11, 1.52) and in the other study by Jeon et al.[19], the corresponding risk ratio was 2.69 (95%CI: 0.61, 11.84). Also, two cohort studies evaluated the association of H. pylori with metabolic syndrome; in the study by Sayilar et al.[52], the odds ratio was 3.61 (95%CI: 0.83, 15.77) and in the other study by Shin et al.[50], the risk ratio based on histological diagnosis for H. pylori was 1.26 (95%CI: 0.69, 2.31) and the risk ratio based on serological diagnosis for H. pylori was 1.12 (95%CI: 0.60, 2.11). After combining the results of these cohort studies concerning metabolic syndrome, the pooled risk ratio was 1.31 with a 95% confidence interval of 1.13 to 1.51. The heterogeneity rate was zero percent (Figures 4a, 4b, and 4c).

Quality Assessment

In the present meta-analysis, the quality of 18 case-control studies and 4 cohort studies was evaluated using JBI critical appraisal tools and the results of which were presented in Tables 3 and 4, respectively. The quality assessment checklist of the case-control studies showed that most of these studies had a high-quality score. Except for the study of Chen et al.[47], which received a score of 6, the rest of the studies had a high-quality score of more than 6 (Table 3). The quality assessment of cohort studies showed high scores for quality of all studies (Table 4).

This meta-analysis aimed to determine the association between H. pylori infection and the occurrence of metabolic syndrome and insulin resistance. The results showed that the presence of H. pylori infection was associated with the risk of metabolic syndrome and insulin resistance in society. These results were in the same line with other studies conducted in the world. The results of previous studies have shown that one of the extra-gastric complications of H. pylori infection was the occurrence of insulin resistance in patients.[53–56] In this instance, various pathophysiologic pathways have been suggested that induce insulin resistance by H. pylori, such as activation of pro-inflammatory substances (CRP, PAI-1, and TNF-α), production of reactive oxygen species (ROS), alteration of ghrelin and leptin levels, and increased production of lipopolysaccharides.[19, 57–59] On the other hand, the virulent strains of H. pylori (cag + with induction of inflammatory factors 71, IL6, CRP) and chronic inflammation affect the insulin-regulating gastroduodenal hormones and ultimately predispose the person to insulin resistance.[19, 60] Inflammation caused by H. pylori affects insulin-producing pancreatic B cells and reduces insulin secretion.[56, 61] By acting on the hormone somatostatin, cag + strains reduce insulin secretion by the pancreas. In addition, H. pylori increase the levels of leptin and ghrelin and predispose people to obesity and diabetes.[56, 62] H. pylori cause type II diabetes by disrupting the production and release of plasma lipoproteins and disrupting glucose tolerance and Hb1Ac levels. On the other hand, diabetics are also exposed to H. pylori because the humoral and cellular immune systems have been damaged and the person is susceptible to the bacterium. Decreased gastric motility in diabetics reduces gastric acid and provides a basis for colonization of H. pylori strains.[63, 64] Finally, it is concluded that cag + strains of H. pylori can predispose people to type II diabetes. Therefore, people with diabetes are always at risk for H. pylori.[63–68] Also, lipopolysaccharides from gram-negative bacteria such as H. pylori, may activate Toll-like receptors and subsequently develop insulin resistance.[69] Finally, all of these factors are among the reasons which can be attributed to the effect of H. pylori infection on the occurrence of insulin resistance and metabolic syndrome. The results of this meta-analysis on determining the association between H. pylori infection and the occurrence of metabolic syndrome were consistent with the meta-analysis of Upala S et al. [70] in which, the results showed that people with H. pylori infection were 1.34 times more likely to develop metabolic syndrome. However, this study was conducted in 2016 and a total of 6 studies had been included in the meta-analysis.[70]

This study had some limitations and strengths. This meta-analysis was an updated study that considered the meta-analysis of Upala S et al. [70] conducted in 2016. Upala S et al. [70] had performed a meta-analysis with six studies, including case-control, cohort, and cross-sectional studies, and finally, they had reported the pooled effect size. One of the main limitations of the study by Upala S et al. [70] was that they did not have a precise search strategy to obtain the initial studies. On the other hand, in epidemiology and methodology, it is not fundamentally correct to combine cross-sectional studies or the effect size obtained from these studies with cohort and case-control studies, and finally to report pooled effect size. Also, the effect size of cohort and case-control studies can be combined only if the prevalence of the desired outcome in the study population is less than 0.05, which has not been observed in the study of Upala S et al. [70] The present meta-analysis was performed with 22 case-control and cohort studies. The results of these two types of studies were separately combined and the pooled effect size of the presence of H. pylori infection with the occurrence of insulin resistance and metabolic syndrome was reported.

One of the limitations of our study was the small number of published cohort studies investigating the association between the presence of H. pylori infection and the occurrence of insulin resistance and metabolic syndrome.

There is a positive association between H. pylori infection and insulin resistance as well as metabolic syndrome. Therefore, health policymakers and clinicians should consider the necessary advice and guidance to develop appropriate treatment in order to eradicate or treat H. pylori infection in people with metabolic syndrome or insulin resistance. However, well-designed clinical trials with appropriate sample sizes are needed to evaluate the effect of eliminating or eradicating H. pylori infection on reducing insulin resistance or metabolic syndrome.

CI: Confidence Interval

OR: Odds Ratio

IDDM: Insulin-Dependent Diabetes Mellitus

NIDDM: Non-Insulin-Dependent Diabetes Mellitus

CINAHL: Cumulative Index to Nursing and Allied Health Literature

EMBASE: Excerpta Medica dataBASE

STROBE: Strengthening the Reporting of Observationally Studies in Epidemiology

PRISMA: Preferred reporting items for systematic reviews and meta-analyses

H. pylori: Helicobacter Pylori

Acknowledgements

Not applicable.

Authors' Contributions

YM conceptualized the idea for this review, formulated the review question, and objectives, assisted with the development of the final search strategy, contributed to the data analysis/ interpretation, and writing the manuscript. MA, HRB, LS, AM, FM and PK contributed to the conceptualization of the final review question, formulation of the review objectives, data analysis/interpretation, and writing the manuscript. All authors read and approved the final manuscript.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Availability of Data and Material

Input data for the analyses are available from the corresponding author on request.

Ethics approval and consent to participate

Not applicable.

Consent for Publication

Not applicable.

Competing Interests

The authors declare that they have no competing interests.

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Due to technical limitations, Table 1, 3 and 4 are only available as a download in the Supplemental Files section.

Table 2: Determining the odds ratio with the confidence interval of association between Helicobacter pylori infection and metabolic syndrome and insulin resistance in case-control studies based on variables of detection methods of infection, study populations, and the continents of the world

Subgroup

Number of studies

Summery Odds Ratio (95% CI)

Between studies

Between subgroups

I²

P _{heterogeneity}

Q

P _{heterogeneity}

Metabolic Syndrome

Method of bacteria detection

Anti-H. pylori antibody

Rapid urease test

C urea breath test (UBT)

5

1

5

1.26 (1.01 – 1.70)

1.26 (0.53 – 3.00)

1.17 (0.02 – 1.35)

0.0 %

-

0.0 %

0.852

-

0.830

1.38

-

1.49

0.19

0.910

Insulin Resistance

Method of bacteria detection

Anti-H. pylori antibody

Rapid urease test (RUT) & Histology

7

3

1.63 (1.25 – 2.12)

1.33 (0.56 – 3.16)

0.0 %

67.1 %

0.990

0.043

2.71

6.64

0.44

0.661

Type of Diabetes

Diabetes Mellitus

Gestational Diabetes

NIDDM

5

1

4

1.19 (1.00 – 1.78)

2.80 (0.39 – 19.92)

1.80 (1.34 – 2.42)

0.0 %

-

0.0 %

0.890

-

0.51

4.37

-

2.33

3.33

0.192

Population

Male

Female

Both

4

7

1.19 (1.00 – 1.78)

2.80 (0.39 – 19.92)

1.80 (1.34 – 2.42)

0.0 %

44.1 %

0.990

0.940

0.152

0.08

0.38

9.36

0.23

0.89

Continent

Asia

America

Africa

Europe

5

7

2

1

1.67 (1.23 – 2.26)

1.47 (0.89 – 2.44)

1.00 (0.26 – 3.77)

2.35 (1.16 – 4.73)

0.0 %

47.6 %

-

0.764

0.930

0.173

-

1.85

0.58

1.91

-

1.72

0.63

Table1and3and4.docx

Association of Helicobacter pylori Infection with the Risk of Metabolic Syndrome and Insulin Resistance: An Updated Systematic Review and Meta-Analysis

Status:

Journal Publication

Version 1

Abstract

Background

Methods

Results

Conclusion

Figures

Introduction

Material And Methods

Results

Discussion

Conclusion

Abbreviations

Declarations

References

Tables

Supplementary Files

Status:

Journal Publication

Version 1