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. 2025 Aug 13:12:1612456.
doi: 10.3389/fmed.2025.1612456. eCollection 2025.

From helicobacter pylori to glucose metabolism: can DOB values serve as a predictive marker?

Affiliations

From helicobacter pylori to glucose metabolism: can DOB values serve as a predictive marker?

Yu Zhou et al. Front Med (Lausanne). .

Abstract

Background: Helicobacter pylori infection and abnormal glucose metabolism are prevalent, interconnected contributors to chronic disease. Although metabolic changes have been studied in infected individuals, the independent association between the delta-over-baseline (DOB) value of the 13C-urea breath test and fasting blood glucose (FBG) remains unclear. We investigated whether DOB could predict abnormal FBG in adults receiving routine health examinations.

Objectives: To assess the association between H. pylori infection and metabolic abnormalities, and to evaluate the predictive utility of the DOB value for glycemic abnormalities.

Methods: In this retrospective study, 594 patients underwent both the 13C-UBT and metabolic parameter assessments. Patients were stratified by DOB values, and metabolic abnormalities were defined by predefined criteria. Logistic regression analyzed the relationship between H. pylori status and metabolic parameters, adjusting for confounders. A restricted cubic spline (RCS) model and receiver operating characteristic (ROC) curve assessed non-linear associations and diagnostic performance of DOB.

Results: Compared with the H. pylori-negative group, the positive group exhibited significantly higher triglyceride (1.667 ± 1.173 vs. 1.447 ± 0.954 mmol/L; p = 0.020) and FBG levels (5.655 ± 1.704 vs. 5.363 ± 1.028 mmol/L; p = 0.024). In multivariable models, H. pylori infection was independently associated with abnormal FBG (OR 2.10; 95% CI 1.30-3.40; p = 0.003) but not with TG abnormalities. The DOB value showed modest overall discriminatory ability for abnormal FBG (AUC = 0.590), with enhanced performance in participants < 40 years (AUC = 0.721).

Conclusion: H. pylori infection is associated with higher fasting glucose and triglyceride levels, and the 13C-UBT DOB value showed modest predictive ability for glycemic abnormalities-especially in adults under 40 (AUC = 0.721). DOB may serve as an adjunct risk-stratification marker in younger populations. However, the single-center, cross-sectional design and lack of lifestyle and mechanistic biomarker data limit causal inference. Prospective multicenter cohort studies with serial UBT, clinical (diet, medications, exercise, socioeconomic factors) and biomarker (cytokines, GLP-1) measurements are needed to validate these findings.

Keywords: Helicobacter pylori; delta-over-baseline; fasting blood glucose; metabolism abnormalities; urea breath test.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

iolin plots compare various biomarkers between H. pylori-positive and H. pylori-negative groups. Panel A shows cholesterol levels with a p-value of 0.538. Panel B displays triglyceride levels with a significant difference, p=0.020. Panel C presents HDL-c levels, p=0.983. Panel D shows LDL-c levels, p=0.915. Panel E depicts fibrinogen levels with a notable difference, p=0.024. Is this a mistake? We wanted to express that there was a difference in FBG levels.
FIGURE 1
Metabolic profiles in H. pylori–positive and negative subjects. Violin plots show the distribution of (A) total cholesterol (CHOL), (B) triglycerides (TG), (C) high-density lipoprotein cholesterol (HDL-C), (D) low-density lipoprotein cholesterol (LDL-C) and (E) fasting blood glucose (FBG). The white dot denotes the group mean, while black dots indicate outliers. TG (1.667 ± 1.173 mmol/L vs. 1.447 ± 0.954 mmol/L; p = 0.020) and FBG (5.655 ± 1.704 mmol/L vs. 5.363 ± 1.028 mmol/L; p = 0.024) were significantly higher in the H. pylori-positive group, whereas CHOL, HDL-C and LDL-C did not differ between groups (all p > 0.05). P-values were obtained with independent-samples t-tests; significance threshold p < 0.05.
Graph showing the odds ratio (OR) with a 95% confidence interval (CI) across different degrees of burden (DOB). The OR line peaks around DOB 15, indicating increased risk, then declines. The confidence interval widens significantly at higher DOB values. Statistical significance is noted with P for overall at 0.004 and P for nonlinear at 0.005.
FIGURE 2
Restricted cubic spline model of the association between DOB and odds of FBG abnormality. The solid curve represents adjusted ORs, shaded area the 95% CI; knots placed at the 5th, 50th and 95th percentiles; non-linearity tested by likelihood-ratio (p < 0.01).
ROC curve illustrating the predictive power of DOB for FGB across age groups. The overall sample has an AUC of 0.590. Age-specific AUCs: under 40 years is 0.721, 40-59 years is 0.546, and 60 years and above is 0.654. The curve shows varying true positive rates against false positive rates.
FIGURE 3
ROC curves depict the discriminatory ability of DOB in the overall cohort (black line; AUC = 0.590) and three age strata: < 40 years (blue line; AUC = 0.721), 40–59 years (gold line; AUC = 0.546), and ≥ 60 years (red line; AUC = 0.654). The diagonal dashed line indicates no-discrimination (AUC = 0.5).

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