Influence of menstrual cycle and oral contraception on taxonomic composition and gas production in the gut microbiome

Abstract

Introduction. Oral contraceptives (OCs) are widely used for birth control and offer benefits such as menstrual cycle regulation and reduced menstrual pain. However, they have also been associated with an increased risk of cancer and reduced bone mass density.Gap Statement. While the gut microbiome is known to interact with endocrine factors, the impact of hormonal OCs on its composition and function remains underexplored. Additionally, we explore the relationship of OC use and the microbiome to gas production, which can cause symptoms and be indicative of poor health.Aim. This study investigates the effects of OCs on the diversity and composition of the gut microbiome and its association with breath hydrogen (H₂) and methane (CH₄) levels.Methodology. We utilized 16S rRNA gene sequencing to analyse faecal samples from 65 women, comparing OC users with non-users at two menstrual cycle time points. Breath tests measured hydrogen and CH₄ production. Data were analysed for microbial diversity, community composition and correlation with gas production.Results. There were no differences in overall microbial diversity between OC users and non-users in samples collected on day 2 of the menstrual cycle. However, on day 21, we found a significant difference in microbial richness, suggesting a cycle-dependent effect of OCs on gut microbiota species richness but not composition. We found a strong correlation between H₂ and CH₄ concentrations and an interaction between OC use and the menstrual cycle on H₂ and CH₄ production. We also identified several taxa associated with both high levels of H₂ and CH₄ production and OC use.Conclusion. Our study highlights the intricate relationships among hormonal contraceptives, the gut microbiota and gas production and connects shifts in the microbiome composition to gastrointestinal symptoms (e.g. gas production) that can impact overall health. This underscores the need for further research on the long-term effects of OCs and for the development of precise therapeutic strategies to address potential adverse effects. Our findings offer new perspectives on the microbiome-hormone-gas production nexus, potentially broadening our understanding of the systemic implications of OCs.

Keywords: human gut microbiome; breath hydrogen; breath methane; oral contraceptives; sex hormones.

Fig. 1.. Distributions of four distinct alpha diversity indices – Faith’s diversity (FD), Observed features (OF), Pielou’s evenness (PE) and Shannon entropy (SE) – were evaluated on day 2 and day 21 for OC users (pink) and control group (yellow). No statistically significant differences were observed in the alpha diversity metrics between the groups, except for OF, which showed a significant interaction between group and day (P=0.04) according to LMEM results in Table 1.

Fig. 2.. NMDS ordination depicting beta diversity of gut microbiome from OC users (pink) and control group (yellow) shows a scattered distribution without clear separation between the OC user and control groups, suggesting a lack of distinct microbial community structures. This was corroborated by a PERMANOVA test, which did not detect statistically significant differences in beta diversity between the two groups (Table 2).

Fig. 3.. Microbial balances define differences between OC users and controls. The bar plot (top) illustrates the log-contrast coefficients for taxa derived from a penalized logistic regression model using the coda4microbiome algorithm. Taxa with coefficients signifying an absolute balance of at least 0.05 are shown, with the length of the bar representing the proportion of each taxon’s contribution. Taxa are ranked by their contribution to the balances, with positive coefficients indicating greater abundance and negative coefficients indicating lesser abundance in OC users. The box plot (bottom) shows the sample distribution of balance values for each specified group.

Fig. 4.. Microbial balances define differences between high and low H₂ groups.

Fig. 5.. Microbial balances define differences between high and low CH₄ groups.

Fig. 6.. Comparison of breath H₂ (ppm) levels in OC users (pink) and control group (yellow) on day 2 and day 21. Box plots display log-transformed breath H₂ concentrations at each time point (in minutes) over a 2 h period following the ingestion of lactulose. Our LMEM revealed a statistically significant interaction between OC users and day on H₂ levels (P<0.001), indicating a distinct response to lactulose at different cycle stages that is not present when considering group or day alone.

Fig. 7.. Comparison of breath CH₄ (ppm) levels in OC users (pink) and control group (yellow) on day 2 and day 21. Box plots display log-transformed breath CH₄ concentrations at each time point (in minutes) over a 2 h period following the ingestion of lactulose, indicating potential differences in CH₄ production between the two groups at different phases of the menstrual cycle. According to our LMEM, both the effect of day and the interaction between group and day were significant (P<0.001).

Fig. 8.. Positive correlation (ρ=0.724, P<0.001) between CH₄ (ppm) and H₂ (ppm) levels measured during breath tests across all subjects. Outliers are labelled based on subject number and, when excluded, the correlation coefficient increased to ρ=0.884.

Fig. 9.. Microbial balances define differences between outlier and normal groups.