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PLOS One logoLink to PLOS One
. 2024 Apr 23;19(4):e0300835. doi: 10.1371/journal.pone.0300835

Causal relationships of Helicobacter pylori and related gastrointestinal diseases on Type 2 diabetes: Univariable and Multivariable Mendelian randomization

Mei Sun 1,2,, Zhe Zhang 3,4,, Jingjing Zhang 5,, Juewei Zhang 6,, Zhuqiang Jia 7,8, Lin Zhao 9, Xin Han 8,10, Xiaohong Sun 11, Junwei Zong 3,*, Ying Zhu 1,*, Shouyu Wang 3,*
Editor: Yasin Sahin12
PMCID: PMC11037534  PMID: 38652719

Abstract

Background

Previous observational studies have demonstrated a connection between the risk of Type 2 diabetes mellitus (T2DM) and gastrointestinal problems brought on by Helicobacter pylori (H. pylori) infection. However, little is understood about how these factors impact on T2DM.

Method

This study used data from the GWAS database on H. pylori antibodies, gastroduodenal ulcers, chronic gastritis, gastric cancer, T2DM and information on potential mediators: obesity, glycosylated hemoglobin (HbA1c) and blood glucose levels. Using univariate Mendelian randomization (MR) and multivariate MR (MVMR) analyses to evaluate the relationship between H. pylori and associated gastrointestinal diseases with the risk of developing of T2DM and explore the presence of mediators to ascertain the probable mechanisms.

Results

Genetic evidence suggests that H. pylori IgG antibody (P = 0.006, b = 0.0945, OR = 1.0995, 95% CI = 1.023–1.176), H. pylori GroEL antibody (P = 0.028, OR = 1.033, 95% CI = 1.004–1.064), gastroduodenal ulcers (P = 0.019, OR = 1.036, 95% CI = 1.006–1.068) and chronic gastritis (P = 0.005, OR = 1.042, 95% CI = 1.012–1.074) are all linked to an increased risk of T2DM, additionally, H. pylori IgG antibody is associated with obesity (P = 0.034, OR = 1.03, 95% CI = 1.002–1.055). The results of MVMR showed that the pathogenic relationship between H. pylori GroEL antibody and gastroduodenal ulcer in T2DM is mediated by blood glucose level and obesity, respectively.

Conclusion

Our study found that H. pylori IgG antibody, H. pylori GroEL antibody, gastroduodenal ulcer and chronic gastritis are all related to t T2DM, and blood glucose level and obesity mediate the development of H. pylori GroEL antibody and gastroduodenal ulcer on T2DM, respectively. These findings may inform new prevention and intervention strategies for T2DM.

Introduction

Type 2 diabetes mellitus (T2DM) is a disease defined by high blood sugar levels and a relative shortage of insulin, as well as insulin resistance and other chronic metabolic illnesses caused predominantly by diabetes, accounting for more than 90% of diabetic patients [1]. Patients with T2DM have a more than 50% chance of developing complications [2], and some studies shows that at least 80% of diabetic patients will die from cardiac complications [3, 4]. Even though T2DM is better understood and treated than it formerly was, the disease’s incidence and prevalence are still rising internationally. Researchers from Sweden made the initial discovery of H. pylori in a culture of human stomach mucosa [5]. Around 60% of people on the planet have H. pylori infections. Cell degeneration, necrosis, and inflammatory cell infiltration can be caused by the inflammation and immunological response brought on by H. pylori infection, and specific antibodies can be found in the serum. TLR1 is primarily localized on the cellular surface, exhibiting heightened expression on immune cells, including macrophages and dendritic cells. It often forms a heterodimer with TLR2, collaboratively engaging in immune responses. The FCGR2A gene, which is classified as a low-affinity receptor for immunoglobulin G (IgG). This receptor is predominantly expressed across various cells within the immune system, encompassing B cells, NK cells, macrophages, and dendritic cells. Both genes bear a significant association with Helicobacter pylori infection [6]. H. pylori is closely related to gastritis, peptic ulcer, gastric cancer and other diseases [7], and H. pylori has been included in the list of a class of carcinogens by the World Health Organization.

T2DM has been recognized as one of the probable illnesses of H. pylori infection in a broad range of observational studies, with 61.5% of H. pylori positive patients having one or more chronic diabetic sequelae [8]. In T2DM patients with concurrent H. pylori infection, H. pylori antibodies could be detected, and 75% of patients experienced gastrointestinal symptoms [9]. H. pylori infection appears to be linked to chronic inflammation, impaired insulin secretion, and higher mean glycosylated hemoglobin levels, all of which increase the risk of T2DM [10, 11]. Additionally, it has been noted that among T2DM patients, obese people have a much greater frequency of H. pylori infection than non-obese patients. However, the correlation between H. pylori infection and the risk of T2DM is still debatable. According to some studies [1113], there is no distinction between diabetic and nondiabetic people in terms of the prevalence of H. pylori infection. This finding may be due to sources of potential bias in observational studies, such as reverse causal consistency and confounding. Therefore, stronger proof is required to show a connection between H. pylori and T2DM.

Typical observational studies cannot demonstrate causation or rule out the impact of confounding factors; they can only show whether there is a correlation between two variables. An epidemiological analytic technique called Mendelian randomization (MR) makes it easier to deduce causes. MR designs use single nucleotide polymorphisms (SNPs), which have a random distribution without being impacted by outside influences and other confounders, as instrumental variables (IVs) for target exposures [14]. As a result, complex disease causal linkages can be rigorously explained using MR designs. MR has been applied more frequently as a result of the expansion of genome-wide association studies (GWAS) and the accessibility of massive amounts GWAS data. In our study, we used seven H. pylori antibodies, as well as chronic gastritis, gastroduodenal ulcer, and gastric cancer, which are closely associated with H. pylori, as exposures, and T2DM as an outcome. Then, we chose obesity, glycosylated hemoglobin (HbA1c), and blood glucose levels as potential mediators to clarify the association of H. pylori and its associated digestive diseases on T2DM and see whether there is a mediating effect, in the hopes of elucidating the causality and offering beneficial treatment and diagnosis recommendations.

Materials and methods

1. Mendelian randomized design

The Structure of the current MR study is shown in Fig 1, and to find the connections between H. pylori and related gastrointestinal diseases and T2DM, we chose the receptors TLR1 (rs10004195) and FCGR2A (rs368433), which are highly correlated with H. pylori IgG antibody seropositivity, as well as six H. pylori antibodies: anti-H. pylori IgG, GroEL, OMP, UREA, CagA, VacA, Catalase, and the three diseases most likely to be induced by H. pylori: chronic gastritis, gastroduodenal ulcer, and gastric cancer as exposure factors, obesity, HbA1c, as well as blood glucose levels were selected as potential mediators, finally, T2DM was selected as an outcome to elucidate the relationship between H. pylori, gastrointestinal diseases and T2DM. For the MR analysis in this work, we employed genetic variants as instrumental factors. Three fundamental presumptions served as the foundation for our MR study’s postulated validity: (1) Correlation hypothesis: genetic variation is closely related to exposure; (2) The independence hypothesis: genetic variation is not associated with any confounding factors that may mediate the way from exposure to outcome; (3) Exclusion-restriction hypothesis: Genetic variation can only affect the result through exposure. In order to exclude the influence of heterogeneity, the random effects model (IVW) was used as the main method in this study, and the MR-Egger and weighted median methods were used for verification [15].

Fig 1. Flowchart of Mendelian randomization analysis conducted in this study.

Fig 1

SVMR analysis investigates the effect of H. pylori infection and related gastrointestinal diseases on T2DM development. MVMR analysis evaluates the roles of potential factors mediating the association between GroEL-positive H. pylori Infection, gastroduodenal ulcer, chronic gastritis, and T2DM.

2. Data sources

Data for the seven antibodies to H. pylori, chronic gastritis, gastroduodenal ulcer, and diabetes and potential mediators were obtained from the GWAS database(https://gwas.mrcieu.ac.uk) [16], and only pooled data from European populations were used to avoid population heterogeneity bias. H. pylori antibody levels of GroEL, OMP, UREA, CagA, VacA and catalase, and blood glucose were obtained from the dataset of the EBI database. Gastroduodenal ulcer, chronic gastritis, gastric cancer, and T2DM were obtained from the Finnish database. Glycated hemoglobin were obtained from the UK Biobank; while the obesity data was collected from GWAS summary datasets. The sample sizes were as Table 1, each GWAS was approved by the appropriate ethics committee.

Table 1. Details of the studies included in the Mendelian randomization analyses.

Phenotype Consortium Ethnicity Sample size GWAS id
H. pylori CagA antibody levels EBI European 985 individuals ebi-a-GCST90006911
H. pylori Catalase antibody levels EBI European 1558 individuals ebi-a-GCST90006912
H. pylori antibody levels EBI European 2716 individuals ebi-a-GCST90006913
H. pylori OMP antibody levels EBI European 2640 individuals ebi-a-GCST90006914
H. pylori UREA antibody levels EBI European 2251 individuals ebi-a-GCST90006915
H. pylori antibody levels EBI European 1571 individuals ebi-a-GCST90006916
Gastroduodenal ulcer FinnGen European 4510 cases, 189,695, controls finn-b-K11_GASTRODUOULC
Chronic gastritis FinnGen European 5,213 cases, 189,695 controls finn-b-K11_CHRONGASTR
Malignant neoplasm of stomach FinnGen European 633 cases, 218,159 controls finn-b-CD2_BENIGN_STOMACH
Obesity GIANT European 2896 cases, 47,468 controls ieu-a-92
HbA1c UK Biobank European 13,586,180 SNPs ukb-d-30750_raw
Blood glucose levels EBI European 400,458 individuals ebi-a-GCST90025986
Type 2 diabetes FinnGen European 24,133 cases, 183,185 controls finn-b-E4_DM2NASCOMP

3. Selection of potential genetic variants

Genetic variants can be obtained in two ways, either directly from GWAS summary statistics or through existing reports in the literature. In this study, genes strongly associated with H. pylori infection were selected based on previously available reports and confirming that existing studies have chosen this approach for H. pylori-associated Mendelian studies [17, 18]. The SNPs rs10004195 at TLR1 (4p14) and rs368433 at FCGR 2A gene (1q23.3) have been identified as genetic variants associated with high H. pylori seropositivity [6]. To check the significance of the allelic score as a tool, the F-statistics of both SNPs were calculated to be greater than 10 (Table 2). Other data on H. pylori antibodies, gastrointestinal diseases, T2DM, and potential mediators were obtained from GWAS summary statistics. A variety of tests are necessary to screen for genetic IVs that are eligible and satisfy the MR hypothesis. First, to boost statistical efficacy and get a sufficient number of IVs, we set the p-value threshold for IVs in this MR study to 5E-05 to screen for SNPs that were associated with exposure and strongly associated with exposure. second, independence was set to eliminate linkage disequilibrium (LD: r2 = 0.001, kb = 10,000, p < 5E-05) and the statistical significance were calculated (F-statistics), with F-statistics greater than 10 indicates the absence of weak instrumental variable bias [9]. Third, to ensure that the effect alleles are members of the same allele, coordinate the exposure and outcome data sets. These exacting processes can be utilized to screen SNPS, which can then be used as IV for further examination.

Table 2. Instrumental SNPs of IgG-positive H. pylori infection and F statistics.

SNP Beta SE EA NEA EAF Pval F-statistics
rs10004195 0.3576744 0.04048331 A T 0.25 1.00E-18 78.059
rs368433 0.3148107 0.05609599 C T 0.16 2.00E-08 31.495

4. Statistical analysis and data visualization

TwoSampleMR, MR-PRESSO, MVMR and forestploter packages in R software are used for analysis, and inverse variance weighting (IVW) is used as the default method to evaluate the causal estimate [19]. For MR Analysis with more than two IVS, two complementary methods MR-Egger and weighted median are used for verification. A P-value less than 0.05 was considered statistically significant. In order to ensure the reliability of the results, we further carried out sensitivity analysis, that is, heterogeneity and Pleiotropyt test. A P-value less than 0.05 indicates the existence of heterogeneity and pleiotropy. Then, the MR-Egger intercept test is used to evaluate the validity of the hypothesis of instrumental variables. The leave-one-out method is used to analyze whether there are SNPS that drive the results independently, and the MR-PRESSO test is used to evaluate whether there are outlier SNPS. For MVMR, we adjusted for T2DM as an outcome and for glucose levels and obesity, respectively, to explore whether they mediated the causal relationship between anti-H. pylori GroEL and gastroduodenal ulcer, respectively, and T2DM.

Results

The number of SNPs screened as instrumental variables significantly associated with exposure through LD ranged from 38 to 444 (S1 File)), and the F-statistic for each SNP included in the study was greater than 10 (Table 3).

Table 3. The number of SNPs and F-statistics of Phenotype.

Phenotype F statistics nSNP
H. pylori CagA antibody levels 19.613 90
H. pylori Catalase antibody levels 18.523 80
H. pylori GroEL antibody levels 18.039 68
H. pylori OMP antibody levels 18.605 86
H. pylori UREA antibody levels 18.691 88
H. pylori VacA antibody levels 18.704 93
obesity 21.959 38
HbA1c 53.192 444
blood glucose 61.164 271
Gastroduodenal ulcer 19.044 92
Chronic gastritis 18.578 84
Malignant neoplasm of stomach 18.693 73

Univariate Mendelian randomization

1. Relationship between potential mediators and T2DM

The relationship between obesity, HbA1c, blood glucose level and T2DM has been validated in many experiments, and to ensure the feasibility of the Mendelian randomization study, we used the validation by IVW method with genetically predicted obesity (P = 0.023, OR = 1.069, 95%CI = 1.008–1.133), HbA1c (P = 1.263E-76, OR = 1.233, 95% CI = 1.206–1.261), and blood glucose levels (P = 8.21E-42, OR = 4.077, 95% CI = 3.327–4.996) were significantly associated with an increased risk of T2DM. To validate this relationship, we then used the MR Egger method and Weighted median, and the results remained significant (obesity: MR Egger: P = 0.023, OR = 1.254, 95% CI = 1.040–1.512; Weighted median: P = 0.00002, OR = 1.080 95% CI = 1.042–1.119; blood glucose level: MR Egger: P = 6.60E-14, OR = 4.331, 95% CI = 3.013–6.225; Weighted median: P = 1.99E-20, OR = 2.916, 95% CI = 2.325–3.656; HbA1c: MR Egger: P = 5.011E-16, OR = 1.195, 95% CI = 1.147–1.246; Weighted median: P = 3.5E-20, OR = 1.130, 95% CI = 1.101–1.159). In the sensitivity analysis results showed heterogeneity in all three, but no pleiotropy, and none of the egger intercepts significantly deviated from 0. Therefore, obesity, HbA1c, and blood glucose levels can be used as potential mediators for Mendelian randomization analysis (Fig 2).

Fig 2. Mendelian randomization results of the effect of potential mediators (obesity, HbA1c, blood glucose level) on T2DM.

Fig 2

2. Effect of H. pylori antibodies on T2DM and its potential mediators

According to the IVW method, genetically predicted anti-H. pylori igG was substantially linked to a higher risk of T2DM (P = 0.006, b = 0.0945, OR = 1.0995, 95% CI = 1.023–1.176), as well as obesity (P = 0.034, OR = 1.03, 95% CI = 1.002–1.055), but the results with HbA1c (P = 0.105, OR = 0.930, 95% CI = 0.852 to 1.015) were not significant enough for causality, and the test for heterogeneity showed that there was no heterogeneity in these results, which was insufficient for other tests and multivariate analyses due to the limitation of the number of snp. Anti-H. pylori GroEL was significantly in connection with an elevated risk of T2DM by the IVW method (P = 0.028, OR = 1.033, 95% CI = 1.004–1.064), in accordance with the results obtained by the MR Egger (P = 0.04, OR = 1.07, 95% CI = 1.003–1.143) and Weighted median (P = 0.004, OR = 1.06, 95% CI = 1.018–1.096). The sensitivity analysis showed the presence of heterogeneity, and the absence of Pleiotropy (Fig 3), none of the Egger intercepts significantly deviated from 0. The MR-PRESSO results showed the absence of an outlier SNP (S2 File). In addition, anti-H. pylori GroEL was associated with increased blood glucose levels(Fig 4), in agreement with IVW (P = 0.020, OR = 1.011, 95% CI = 1.002–1.021) and Weighted median (P = 0.029, OR = 1.014, 95% CI = 1.001–1.027) methods, In contrast, it was not significant in MR Egger method (P = 0.111, OR = 1.017, 95% CI = 0.997–1.038), Concerning the sensitivity analysis, the results showed no heterogeneity and pleiotropy, none of the egger intercepts significantly deviated from 0, and the MR-PRESSO results also showed the absence of outlying SNP (S2 File), in addition, the leave-one-out method of alignment analysis showed the absence of a single SNP causes the causal consequences of anti-H. pylori GroEL on T2DM and blood glucose levels(Fig 5). However, anti-H. pylori GroEL was not causally associated with obesity and HbA1c, and none of the other antibody- H. pylori were causally associated with T2DM.

Fig 3. Mendelian randomization results of the effect of H. pylori antibodies, gastroduodenal ulcer, chronic gastritis, Malignant neoplasm of stomach on T2DM.

Fig 3

Fig 4. Mendelian randomization results of the effect of H. pylori antibodies, gastroduodenal ulcer, chronic gastritis on potential mediators (obesity, HbA1c, blood glucose level).

Fig 4

Fig 5.

Fig 5

(A, B) Mendelian randomization result of the leave-one-out method of anti-H.pylori GroEL on T2DM and blood glucose levels. (C, D) Mendelian randomization result of the leave-one-out method of gastroduodenal ulcer on T2DM and obesity. (E) Mendelian randomization results of the leave-one-out method of chronic gastritis on T2DM.

3. Impact of gastrointestinal disorders on T2DM and potential intermediaries

Genetically predicted gastroduodenal ulcer and chronic gastritis were both in connection with an elevated risk of T2DM, nevertheless, there was no causal relationship between Malignant neoplasm of stomach and T2DM (Fig 3). By using the IVW method, gastroduodenal ulcer was found to be significantly associated with an increased risk of T2DM (P = 0.019, OR = 1.036, 95% CI = 1.006–1.068), but not relevant when utilizing the weighted median (P = 0.410, OR = 1.016, 95%CI = 0.978–1.055) or MR-Egger (P = 0.071, OR = 1.056, 95%CI = 0.996–1.120). The assessment of the heterogeneity and pleiotropy, revealed the presence of heterogeneity and absence of pleiotropy. The egger intercept did not significantly deviate from 0, the leave-one-out permutation analyses revealed the lack of a single SNP with a causal effect on T2DM, the MR-PRESSO results also revealed the absence of outlier SNPs (S2 File)). Furthermore, the gastroduodenal ulcer was also linked to an increased risk of obesity as determined by the IVW method (P = 0.009, OR = 1.204, 95% CI = 1.047 to 1.385), but was not significant in the other two methods, there was no heterogeneity and pleiotropy (Fig 4), and the leave-one-out method showed the absence of individual SNPs driving the causal effect on obesity (Fig 5). According to the results, the gastroduodenal ulcer was not causally associated with HbA1c and blood glucose levels. Regarding the chronic gastritis lesions, the results showed a significant link between chronic gastritis and increased risk of T2DM (P = 0.005, OR = 1.042, 95% CI = 1.012–1.074), and the result agreed with weighted median approach (P = 0.042, OR = 1.046, 95% CI = 1.002–1.092). While in MR Egger the result was not significant, sensitivity analysis showed no heterogeneity or pleiotropy, and the Egger intercept was almost close to 0, the leave-one-out method also showed that there was no snp that individually drives a causal effect on T2DM (Fig 5), MR-PRESSO results showed that there was no standing group of snp (S2 File). No causal relationship between chronic gastritis and any of the three candidate mediators was revealed (Fig 4).

Multivariate Mendelian randomization

1. Mediating relationship between anti-H. pylori GroEL and blood glucose levels with T2DM

MVMR was carried out to determine whether blood glucose levels were a mediating factor in the association between GroEL antibody-positive H. pylori and T2DM. When blood glucose levels were adjusted, the connection between T2DM and anti-H. pylori GroEL vanished (P = 0.131, OR = 1.085, 95% CI = 0.976–1.205) in IVW method, but the link between blood glucose levels and the disease was still persisted (P = 3.82E-41, OR = 4.071, 95% CI = 3.317–4.996). The results of MVMR using Lasso methods showed consistent results with the IVW method (Fig 6).

Fig 6. Multivariable MR result of causal relationships of anti-H.pylori GroEL and blood glucose levels on T2DM.

Fig 6

2. Mediating relationship between Gastroduodenal ulcer and obesity with T2DM

The relationship between T2DM and obesity-mediated gastroduodenal ulcer was examined using MVMR. The results revealed that while the relationship between gastroduodenal ulcer and T2DM vanished after combining the instrumental variables of obesity and gastroduodenal ulcer, the association between obesity and T2DM remained substantial. (P = 0.541, OR = 1.033, 95% CI = 0.931–1.146). Similarly, the MVMR results of Lasso were consistent with IVW method (Fig 7).

Fig 7. Multivariable MR result of causal relationships of gastroduodenal ulcer and obesity on T2DM.

Fig 7

Discussion

Although evidence indicates that H. pylori infection is linked to a higher likelihood of T2DM, the exact cause and underlying mechanisms remain unknown. We investigated the causal relationships among seven different types of H. pylori antibodies, gastroduodenal ulcer, chronic gastritis, gastric cancer, and T2DM by using univariate Mendelian randomization, and we investigated whether these causal relationships were mediated using multivariate Mendelian randomization. The results showed that the relationship among anti-H. pylori IgG, anti-H. pylori Groel, gastroduodenal ulcer, chronic gastritis and type 2 diabetes is causally related. In addition, fasting glucose and obesity, respectively, act as mediators in the relationships between anti-H. pylori Groel, gastroduodenal ulcer, and T2DM.

Antibodies anti-H. pylori are found in the infected patients. It is reported, that a higher levels of H. pylori antibodies anti-H. pylori is linked to T2DM [20]. An observational study found that more than 75% of diabetic patients had elevated H. pylori antibodies and from gastric problems [10]. SNP rs 10004195 of the Toll-like receptor 1 (TLR 1) gene at 4p 14 and SNP rs368433 of the FCGR 2A gene at 1Q 23.3 have been identified as genetic variants with the strongest association for H. pylori sero-positive rates [6]. TLR1’s A allele has been linked to an increase in H. pylori infections, and FCGR polymorphisms have been linked to a number of persistent bacterial infections [18, 21]. By analyzing the original literature, it was discovered that these two receptors were taken from H. pylori serum igG antibodies. These two receptors were studied by Mendelian randomization in prior relevant studies on behalf of H. pylori as an exposure factor [17, 22]. Mendelian study of these two receptors with T2DM and potential mediators revealed a strong association between them and an elevated risk of both T2DM and obesity. However, due to the limited number of SNPs, it was not sufficient to carry out the next step of the multivariate Mendelian randomization study; thus, we reasonably hypothesized by combining previous reports in the literature and our findings that obesity may be a mediating factor in the increase of T2DM by anti-H. pylori igG, and our speculation is consistent with a study on the correlation of H. pylori and obesity with T2DM, which indicated that the prevalence of H. pylori infection is increased in obese patients with T2DM, and obese patients with T2DM had a greater rate of H. pylori infection [9].

GroEL is a chaperone protein that is necessary for the proper folding of several proteins in bacteria [23]. Previous research has revealed that GroEL is a novel H. pylori virulence factor that is extensively expressed in most H. pylori strains and may act as a possible indicator for high-risk H. pylori infections. Antibodies against GroEL are linked to H. pylori infections and are capable of sticking to gastric epithelial cells and triggering inflammatory responses [24], which is an independent predictor of gastric lesion progression [25]. Furthermore, GroEL is cross-reactive in humans and H. pylori, and this cross-reactive antibody may contribute to the inflammatory response, raising the risk of T2DM [26]. Our MR study suggest that GroEL antibodies not only increase the risk of T2DM, but also raise blood glucose levels, which is similar with the findings of Ningning You et al. on H. pylori and blood glucose [27], who demonstrated that H. pylori infection is a distinct risk factor for elevated blood glucose levels in nondiabetic individuals, and that persistent H. pylori infection leads to elevated fasting plasma glucose and TG/HDL levels, which give rise to the development of T2DM. This could be because H. pylori infection increases the consumption of a high-fat diet, which alters the diversity of key intestinal bacteria, causing an imbalance in intestinal homeostasis, increasing lipid metabolism, and ultimately leading to an imbalance in glucose metabolism [28], and previous research has shown that intestinal microbiology plays a significant role in the hyperglycemia brought on by H. pylori [29]. Therefore, it is imperative to get eradicated of H. pylori infections as soon as they are found in order to prevent T2DM and blood glucose abnormalities from developing as a result of chronic infections.

The role of H. pylori infection in peptic ulcer, gastric cancer, gastritis, and other gastrointestinal disorders is becoming more and more clearly recognized with the passage of time [30]. In an observational study, as many as 75% of diabetic patients responded with significant gastrointestinal symptoms [31, 32], presenting with dysphagia, reflux, constipation, stomach discomfort, nausea, vomiting, and diarrhea [8]. It has been reported that the release of gastric-related hormones may be influenced by H. pylori-induced gastritis, and among these hormones, leptin, hunger hormone, gastrin, and growth inhibitor all affect the susceptibility to diabetes and promote obesity and diabetes [33, 34]. The following are some potential mechanisms at play: High levels of leptin may hamper function of pancreatic islet, inhibit insulin production in response to glucose and cause human pancreatic B-cell death via activating c-JNK [35]; gastrin increases food-related and glucose-stimulated insulin release [36], growth inhibitor controls pancreatic insulin secretion and prevents insulin release, while starvation hormone lowers energy expenditure and encourages weight gain [37]. In our study, we carried out a Mendelian randomization study of the three diseases most likely to be induced by H. pylori with T2DM, and the results showed that gastric cancer was not causally related to T2DM, while gastroduodenal ulcer and chronic gastritis were associated with the development of T2DM, and in order to further explore the mechanism of the occurrence of this causality, we compared the two diseases with the T2DM development, respectively. Mendelian analysis of obesity, HbA1c and blood glucose levels, respectively, which showed that gastroduodenal ulcer was a risk factor for increased risk of obesity, so we hypothesized that obesity might be a mediator between gastroduodenal ulcer and T2DM, and then we carried out the validation, and the result was in line with our speculation that gastroduodenal ulcer mediated T2DM through obesity, which was in line with the results of previous results of a Mendelian study on the association between peptic ulcer and obesity [38], therefore, obese patients with gastroduodenal ulcer should be carefully managed to prevent T2DM.

In conclusion, among the exposures adopted in this study, anti-H. pylori IgG, GroEL, gastroduodenal ulcer and chronic gastritis were causally associated with T2DM, which suggests a close relevance between gastrointestinal disorders and the condition. Patients with H. pylori should pay close attention to T2DM-related indicators to achieve early detection and prompt treatment. Additionally, this study and other article reports highlight the crucial relationship between obesity and T2DM, thus people with H. pylori infection must pay attention to weight control to stop the condition from progressing.

The strengths of this study are the selection of data from larger studies, the full inclusion of indicators of H. pylori infection and associated gastrointestinal disorders as exposures, the first exploration of the association between H. pylori and T2DM by Mendelian randomization, and the use of multivariate MR analyses to explore mediating pathways in order to identify a number of possible mechanisms, filling a gap in the randomized controlled trials. There are also some limitations of this study. First, to obtain sufficient instrumental variables, the P-value threshold chosen for IV was 5E-05, which may introduce a weak instrumental bias to the overall estimates. Second, there is a small dataset on H. pylori infection in the GWAS database, and although we used snps and antibodies strongly associated with it to do the study and get positive results, there is still a need for more comprehensive data to line up a broader study on H. pylori. Third, in order to avoid the bias of population heterogeneity, we only based the GWAS summary statistics on the population of European descent, and the applicability of these results to other ethnic groups needs to be further explored.

Conclusion

Our research discovered that H. pylori IgG antibody, H. pylori GroEL antibody, gastroduodenal ulcer, and chronic gastritis are all linked to type 2 diabetes. Additionally, blood glucose levels and obesity serve as intermediaries between H. pylori GroEL antibody, gastroduodenal ulcerand type 2 diabetes, respectively. This study indicates that H. pylori eradication therapy can decrease the risk of developing type 2 diabetes. Furthermore, controlling blood sugar and weight can help reduce the risk of developing type 2 diabetes in individuals with H. pylori infection and gastroduodenal ulcer.

Supporting information

S1 File. SNPS information for tool variables.

SNPS for Mendelian randomization analysis after linkage imbalance and adjustment of p-values for all instrumental variables.

(ZIP)

pone.0300835.s001.zip (290.2KB, zip)
S2 File. Results of MRPRESSO by R software.

The original MRPRESSO result obtained by R software.

(DOCX)

pone.0300835.s002.docx (15.7KB, docx)

Acknowledgments

We gratefully acknowledge the authors and participants of all GWASs from which we used summary statistics data.

Data Availability

The minimal data for this study are publicly accessible from the GWAS database (https://gwas.mrcieu.ac.uk). To access the minimal data, please visit the following URLs: Helicobacter pylori CagA antibody levels: https://gwas.mrcieu.ac.uk/datasets/ebi-a-GCST90006911/; Helicobacter pylori Catalase antibody levels: https://gwas.mrcieu.ac.uk/datasets/ebi-a-GCST90006912/; Helicobacter pylori GroEL antibody levels: https://gwas.mrcieu.ac.uk/datasets/ebi-a-GCST90006913/; Helicobacter pylori OMP antibody levels: https://gwas.mrcieu.ac.uk/datasets/ebi-a-GCST90006914/; Helicobacter pylori UREA antibody levels: https://gwas.mrcieu.ac.uk/datasets/ebi-a-GCST90006915/; Helicobacter pylori VacA antibody levels: https://gwas.mrcieu.ac.uk/datasets/ebi-a-GCST90006916/; Gastroduodenal ulcer: https://gwas.mrcieu.ac.uk/datasets/finn-b-K11_GASTRODUOULC/; Chronic gastritis: https://gwas.mrcieu.ac.uk/datasets/finn-b-K11_CHRONGASTR/; Malignant neoplasm of stomach: https://gwas.mrcieu.ac.uk/datasets/finn-b-CD2_BENIGN_STOMACH/; Obesity: https://gwas.mrcieu.ac.uk/datasets/ieu-a-92/; HbA1c: https://gwas.mrcieu.ac.uk/datasets/ukb-d-30750_raw/; Blood glucose levels: https://gwas.mrcieu.ac.uk/datasets/ebi-a-GCST90025986/; Type 2 diabetes: https://gwas.mrcieu.ac.uk/datasets/finn-b-E4_DM2NASCOMP/.

Funding Statement

This study was supported by the National Natural Science Foundation of China (82074426, 82104864, 82204822), Natural Science Foundation of Liaoning Province (2021-BS-215, 2022-MS-25, 2023-MS-13), Liaoning Revitalization Talents Program (XLYC1802014), Key Research and Development Program of Liaoning Province (2017226015), Natural Science Foundation of Tibet Autonomous Region (XZ202301ZR0030G, XZ2023ZR-ZY82(Z)). There was no additional external funding received for this study.

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Decision Letter 0

Yasin Sahin

31 Jan 2024

PONE-D-23-39158Causal relationships of Helicobacter pylori and related gastrointestinal diseases on Type 2 diabetes: Univariable and Multivariable Mendelian randomizationPLOS ONE

Dear Dr. wang,

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This study was supported by the National Natural Science Foundation of China (82074426, 82104864, 82204822), Natural Science Foundation of Liaoning Province (2021-BS-215, 2022-MS-25, 2023-MS-13), Liaoning Revitalization Talents Program (XLYC1802014), Liaoning Key Research and Development Planning Project (2017226015), Basic Research Projects of Liaoning Provincial Department of Education (LJKMZ20221286), Naural Science Foundation of Tibet Autonomous Region and Regional Science(XZ202301ZR0030G, XZ2023ZR-ZY82(Z)) and Technology Project of Naqu City.

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Reviewer #2: Partly

**********

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Reviewer #1: I Don't Know

Reviewer #2: No

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Reviewer #1: Authors have done a commendable job in preparing this manuscript. I am unable to comment on statical analysis. Ref. no 5 should be looked at and corrected. The related statement saying " Sweden " should be corrected. All other ref. should be reviewed and make sure the statements are correct.

The manuscript should be corrected by an English-speaking writer.

Reviewer #2: The study design is interesting by using several statistical methods to assess the relationship between H.pylori infection and the pathologies associated, and other mediators with the risk of developing type 2 diabetes. However, the writing of the article is not good, difficult to read and understand, requirs a revision, use of simple and scientific words. I've attached the article with remarks marked in red and green.

*Study concept: good

*Statistical analyses: good

*Writting: difficult to read and understand, grammatical errors, revision is required (article not ready for publication).

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Attachment

Submitted filename: PONE-D-23-39158_reviewer.docx

pone.0300835.s003.docx (416.3KB, docx)
PLoS One. 2024 Apr 23;19(4):e0300835. doi: 10.1371/journal.pone.0300835.r002

Author response to Decision Letter 0


1 Mar 2024

Dear Editor and Reviewers,

First and foremost, we would like to express our heartfelt gratitude for your recent correspondence. We are sincerely thankful for the constructive feedback provided by the reviewers regarding our manuscript. Your insights have been immensely valuable to us as we continue to refine and improve our work. The insights offered have been immensely valuable and have greatly contributed to the enhancement of our paper. In light of the reviewers' suggestions, we have undertaken extensive revisions aimed at strengthening the persuasiveness of our work. The changes made to the manuscript are reflected in the Revised manuscript (marked-up copy), and we have outlined our responses to the comments from our two kind and approachable reviewers below:

Journal Requirements:

1.When submitting your revision, we need you to address these additional requirements.

We ensure that the format of the revised article meets the requirements of the journal.

2. We note that the grant information you provided in the ‘Funding Information’ and ‘Financial Disclosure’ sections do not match.

Following the resubmission, the 'Funding Information' section has been duly provided and corrected.

3. Please provide an amended statement that declares all the funding or sources of support (whether external or internal to your organization) received during this study, as detailed online in our guide for authors at http://journals.plos.org/plosone/s/submit-now. Please also include the statement “There was no additional external funding received for this study.” in your updated Funding Statement.

We have provided a revised statement in our cover letter stating all sources of funding or support.

Additional Editor Comments:

Thank you for the study. I invite you to resubmit your manuscript after addressing two reviewers’ comments. When resubmitting your manuscript, please carefully consider all issues mentioned in the reviewers' comments, outline every change made point by point, and provide suitable rebuttals for any comments not addressed.

We are profoundly grateful for your meticulous review of our manuscript. Your concerns have been duly noted, and we are appreciative of the insightful suggestions that have greatly contributed to improving our work. In response to your feedback, we have undertaken comprehensive revisions to the earlier draft, ensuring that the issues raised have been thoroughly addressed.

COMMENTS TO THE AUTHOR:

1.Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Partly

Reviewer #2: Partly

We are grateful for your careful review and evaluation of the content of our manuscript. We highly value the concerns you have raised regarding the technical soundness of our paper and the support of data for our conclusions.

Our research is methodologically sound, and the data derived robustly support the conclusions drawn. Our study employed the Mendelian randomization approach, a causal inference method based on genetic variants. Its technical reliability hinges on three core assumptions: the relevance assumption ensures a strong correlation between the chosen SNPs and the exposure factor; the independence assumption requires that the SNPs are independent of confounding factors; and the exclusion restriction assumption suggests that the SNPs affect the outcome solely through the exposure. These assumptions collectively underpin the theoretical foundation of Mendelian randomization, enabling researchers to leverage the natural random assortment of genes to investigate causal relationships between specific biological factors and diseases.

In terms of the extent to which the data bolster the conclusions, Mendelian randomization studies utilize genetic data as instrumental variables, akin to the randomization process in randomized controlled trials, thereby aiding scientists in exploring the causal links between an exposure and an outcome. This methodology allows researchers to employ large, publicly available genome-wide association datasets for causal inference, offering fresh avenues for research in fields such as neurology. A key advantage of the Mendelian randomization method lies in its effect estimates being unaffected by confounding factors and reverse causation, thus providing clearer evidence to substantiate particular conclusions. In summary, the Mendelian randomization method ensures the scientific integrity and credibility of its analysis through rigorous hypothesis testing and analytical procedures.

We would like to express our gratitude once more for your invaluable feedback, which is essential for enhancing the quality of our manuscript.

2.Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: I Don't Know

Reviewer #2: No

We are deeply appreciative of the review process and the insights provided by the reviewers. Recognizing the importance of statistical rigor in our manuscript, we take the feedback seriously, especially given that one reviewer indicated uncertainty and the other noted concerns with our statistical analysis. Our research has incorporated appropriate and rigorous statistical analyses. Mendelian randomization (MR) relies on a series of assumptions, including the relevance of genetic variants to risk factors, the independence of genetic variants from confounding factors, and the exclusion restriction that genetic variants affect outcomes only through the risk factors. The validation and analysis of these assumptions are closely related to statistics. In our study, we have conducted: (1) Relevance assessment: We examined the strength of association between genetic variants and risk factors through MR methods, using inverse-variance weighting (IVW) to estimate the effect of exposure on outcomes by weighted averaging the effect sizes of each genetic variant, with weights typically based on the inverse of the standard error of each variant's effect size (i.e., inverse variance), and regression analysis with the MR-Egger method to adjust for directional pleiotropy. (2) Independence and exclusion restriction tests: In our analysis, we employed sensitivity analyses such as heterogeneity and pleiotropy tests to verify the reliability of our results. (3) Causal inference analysis: At the heart of MR studies is the use of genetic data as an instrumental variable to explore the causal relationship between exposure and outcomes. This involves statistical methods such as linear regression and logistic regression to estimate the impact of genetic variants on disease risk. Therefore, in MR studies, the results of statistical analysis are correctly interpreted and presented, ensuring the scientific integrity and reliability of the research. The application of these methods enables MR studies to more precisely estimate the causal relationships between exposure factors and diseases, helping to overcome issues of confounding and reverse causation inherent in traditional observational studies. Through these advanced statistical techniques, MR studies provide robust evidence to support public health policy formulation and clinical practice.

Overall, statistical analysis plays a crucial role in the Mendelian randomization method; it not only helps to validate key assumptions but also serves to estimate and explain the influence of genetic variants on disease risk. Through these analyses, researchers can gain a better understanding of the causal relationships between biological factors and diseases.

Thank you once again for your constructive criticism, which plays a crucial role in enhancing the quality of our research.

3.Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #1: Yes

Reviewer #2: Yes

We are deeply grateful for your feedback and affirmation. Indeed, we have ensured that all pertinent data underlying the findings in our manuscript are fully accessible to the public. The availability of these data is critical for the replication of our results and for fostering further research endeavors.

Thank you once again for your support and engagement with our work.

4. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #1: No

Reviewer #2: No

We are truly grateful for your careful review and constructive feedback regarding our manuscript. We acknowledge that, as pointed out, there is room for improvement in terms of clarity and adherence to standard English. Rest assured, we will undertake a thorough revision to enhance the clarity and readability of our document, ensuring it aligns with the norms of standard English. We are extremely grateful to Reviewer #2 for taking the valuable time to polish the language of this article. We have made our best efforts to improve the manuscript, refining the text throughout based on the reviewer's invaluable suggestions. These changes do not affect the content and framework of the paper; the modifications made after polishing are listed in the Revised manuscript (marked-up copy). Here, we would like to extend our heartfelt thanks once again to the reviewer for their enthusiastic work, and we hope that these revisions will be approved.

5. Review Comments to the Author

Reviewer #1: Authors have done a commendable job in preparing this manuscript. I am unable to comment on statical analysis. Ref. no 5 should be looked at and corrected. The related statement saying " Sweden " should be corrected. All other ref. should be reviewed and make sure the statements are correct. The manuscript should be corrected by an English-speaking writer.

We extend our heartfelt gratitude for your thorough review and the evaluation of our manuscript. We sincerely appreciate the invaluable suggestions and feedback you have provided throughout the review process. Thank you very much for your valuable feedback. Taking into account your suggestions, we have polished the language of the article in conjunction with the corrections proposed by a native English-speaker and have uploaded the revised paper. Thanks again for your advice, which avoids mistakes and makes the article more perfect. We wish you success in all your endeavors!

Reviewer #2: The study design is interesting by using several statistical methods to assess the relationship between H.pylori infection and the pathologies associated, and other mediators with the risk of developing type 2 diabetes. However, the writing of the article is not good, difficult to read and understand, requirs a revision, use of simple and scientific words. I've attached the article with remarks marked in red and green.

We are deeply grateful for your meticulous review and appraisal of our manuscript. We are particularly honored by your recognition of the intriguing study design, which is greatly appreciated. Moreover, we extend our heartfelt thanks for the invaluable suggestions and edits you have contributed towards refining the article. We are extremely grateful for your time in reviewing this article and especially for your help in polishing its language. We have revised the article according to your suggestions, and the updated version has been uploaded. Thank you once again for your valuable input and for the language improvements you've made. Wish you the best!

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Yes, we would like to publish the peer review history.

In closing, we wish to express our heartfelt thanks once more for your diligent work. The professional opinions and guidance you have provided are not only instrumental in improving the quality of our manuscript but also serve as invaluable direction for our research trajectory. We extend our deepest respect for your dedication and contributions.

We eagerly look forward to further guidance and feedback on our revised manuscript.

With warm regards,

Shouyu Wang

Attachment

Submitted filename: response.docx

pone.0300835.s004.docx (18.8KB, docx)

Decision Letter 1

Yasin Sahin

6 Mar 2024

Causal relationships of Helicobacter pylori and related gastrointestinal diseases on Type 2 diabetes: Univariable and Multivariable Mendelian randomization

PONE-D-23-39158R1

Dear Dr. Shouyu wang,

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PLOS ONE

Additional Editor Comments (optional):

Thank you for the study. The authors did an appropriate point-by-point response to the reviewers.

Reviewers' comments:

Acceptance letter

Yasin Sahin

3 Apr 2024

PONE-D-23-39158R1

PLOS ONE

Dear Dr. wang,

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PLOS ONE

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    S1 File. SNPS information for tool variables.

    SNPS for Mendelian randomization analysis after linkage imbalance and adjustment of p-values for all instrumental variables.

    (ZIP)

    pone.0300835.s001.zip (290.2KB, zip)
    S2 File. Results of MRPRESSO by R software.

    The original MRPRESSO result obtained by R software.

    (DOCX)

    pone.0300835.s002.docx (15.7KB, docx)
    Attachment

    Submitted filename: PONE-D-23-39158_reviewer.docx

    pone.0300835.s003.docx (416.3KB, docx)
    Attachment

    Submitted filename: response.docx

    pone.0300835.s004.docx (18.8KB, docx)

    Data Availability Statement

    The minimal data for this study are publicly accessible from the GWAS database (https://gwas.mrcieu.ac.uk). To access the minimal data, please visit the following URLs: Helicobacter pylori CagA antibody levels: https://gwas.mrcieu.ac.uk/datasets/ebi-a-GCST90006911/; Helicobacter pylori Catalase antibody levels: https://gwas.mrcieu.ac.uk/datasets/ebi-a-GCST90006912/; Helicobacter pylori GroEL antibody levels: https://gwas.mrcieu.ac.uk/datasets/ebi-a-GCST90006913/; Helicobacter pylori OMP antibody levels: https://gwas.mrcieu.ac.uk/datasets/ebi-a-GCST90006914/; Helicobacter pylori UREA antibody levels: https://gwas.mrcieu.ac.uk/datasets/ebi-a-GCST90006915/; Helicobacter pylori VacA antibody levels: https://gwas.mrcieu.ac.uk/datasets/ebi-a-GCST90006916/; Gastroduodenal ulcer: https://gwas.mrcieu.ac.uk/datasets/finn-b-K11_GASTRODUOULC/; Chronic gastritis: https://gwas.mrcieu.ac.uk/datasets/finn-b-K11_CHRONGASTR/; Malignant neoplasm of stomach: https://gwas.mrcieu.ac.uk/datasets/finn-b-CD2_BENIGN_STOMACH/; Obesity: https://gwas.mrcieu.ac.uk/datasets/ieu-a-92/; HbA1c: https://gwas.mrcieu.ac.uk/datasets/ukb-d-30750_raw/; Blood glucose levels: https://gwas.mrcieu.ac.uk/datasets/ebi-a-GCST90025986/; Type 2 diabetes: https://gwas.mrcieu.ac.uk/datasets/finn-b-E4_DM2NASCOMP/.


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