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Home»Men's Health»How a dose of antibiotic can reshape your gut microbiome for years
Men's Health

How a dose of antibiotic can reshape your gut microbiome for years

healthtostBy healthtostMarch 18, 2026No Comments4 Mins Read
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How A Dose Of Antibiotic Can Reshape Your Gut Microbiome
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Large-scale human data reveal that even a single course of antibiotics can leave a measurable microbial footprint years later, raising important questions about long-term health effects and prescribing practices.

Study: Antibiotic use and gut microbiome composition linked from individual-level prescription data of 14,979 subjects. Image credit: marevgenna / Shutterstock

In a recent study published in the journal Nature Medicinethe researchers found that antibiotic effects on the gut microbiome may persist much longer than expected. Linking data from the Swedish prescription register with stool metagenomic profiles from nearly 15,000 adults in multiple population groups, the study showed that even a single course of antibiotics taken four to eight years earlier was associated with lasting differences in microbiome composition.

These findings highlight the potential for prolonged disruption of the microbiome and underscore the need for careful antibiotic use, as even routine prescriptions can have lasting health effects.

Disruption of the gut microbiome and risk of chronic disease

Disturbances in the gut microbial ecosystem are increasingly recognized as a key factor in a wide range of health conditions, including cardiometabolic diseases, autoimmune disorders, and colon cancer. Antibiotics are a major driver of these imbalances, and repeated or prolonged use has been linked to higher risks of obesity, type 2 diabetes, and cardiovascular disease.

Small intervention studies have shown rapid decreases in microbial diversity and shifts in essential bacterial groups after treatment. However, these findings largely reflect short-term effects. As antibiotic use remains widespread, understanding the long-term effects on gut microbial communities has become a critical research priority, although robust large-scale evidence has been limited.

Methods for Population Study Design and Microbiome Analysis

In this population-based study of 14,979 people, researchers looked at the effect of oral antibiotic use in the previous eight years on the microbial composition of the gut. They linked prescription data from the Swedish National Prescription Drug Register (NPDR) with faecal metagenomic data from three groups: CArdioPulmonary bioImage Study (SCAPIS), Swedish Infrastructure for Medical Population-based Life-course and Environmental Research (SIMPLER) and Malmö Offspring Study (MOS).

The team assessed antibiotic exposure at three time points: within 1 year, 1 to 4 years, and 4 to 8 years before sampling. Participants with recent antibiotic use, inflammatory bowel disease, or chronic lung disease were excluded. Fecal samples were subjected to deep shotgun metagenomic sequencing and microbial diversity was quantified using indices such as the Shannon index and the inverse Simpson index. Taxonomic classification was performed using the Genome Taxonomy Database.

Multivariate regression models assessed associations between antibiotic exposure and microbiome diversity, adjusting for confounders such as age, sex, body mass index (BMI), smoking status, education, and comorbidities. The models also accounted for medications such as proton pump inhibitors (PPIs), statins, metformin, beta-blockers, antipsychotics, and selective serotonin reuptake inhibitors (SSRIs).

Sensitivity analyzes examined alternative exclusion criteria, while spline-based models explored microbiome recovery over time. Subgroup analyzes were conducted by age and sex.

Persistent microbiome changes after antibiotic exposure

Antibiotic use was common, with approximately 70–74% of participants receiving at least one prescription in the previous eight years. Broad-spectrum penicillins, penicillin V, and tetracyclines were most commonly used.

The greatest reductions in microbial diversity occurred within 1 year of antibiotic use. However, significant associations remained for exposures one to four years earlier and even four to eight years earlier. Each additional course was associated with a further reduction in diversity. Notably, even a single course conducted years earlier was linked to long-term differences in the microbiome.

Clindamycin, fluoroquinolones and flucloxacillin showed the strongest and most persistent effects. These antibiotics were associated with changes in the relative abundance of up to about 10–15% of microbial species. Beneficial items such as Alistipes communis and Odoribacter splanchnicus was rejected. Conversely, species associated with metabolic risk, incl Ruminococcus gnavus, Flavonifractor plautiiand Eggerthella lentaincreased in abundance. Penicillin V showed relatively little effect.

Microbiome recovery was faster within the first 2 years after antibiotic use, but slowed thereafter and was often incomplete. Recovery varied by antibiotic class, sex, and age, suggesting that microbiome resistance differs among individuals. Sensitivity analyzes confirmed the robustness of these findings.

α, Μετρικές ποικιλότητας μικροβιώματος (Δείκτης Shannon, πλούτος ειδών και αντίστροφος (Inv.) Δείκτης Simpson) για κάθε πρόσθετο κύκλο οποιουδήποτε αντιβιοτικού 4-8 χρόνια, 1-4 χρόνια και <1 έτος πριν από τη δειγματοληψία κοπράνων. Ο εκτιμώμενος οριακός μέσος όρος (EMMs) της ποικιλομορφίας λήφθηκε με τη χρήση μοντέλων παλινδρόμησης, με την έκθεση σε αντιβιοτικά μοντελοποιημένα με χρήση περιορισμένων κυβικών γραμμών και προσαρμογή για ηλικία, φύλο, κάπνισμα, εκπαίδευση, χώρα γέννησης, πλάκα ανάλυσης ανά τοποθεσία, ΔΜΣ, Δείκτη Συννοσηρότητας Charlson, Πολυφαρμακία και χρήση PPIs αντιψυχωσικά (n = 14.974). Τα τετράγωνα αντιπροσωπεύουν τα EMM και εμποδίζουν τα διαστήματα εμπιστοσύνης 95%. β, Ζευγαρωμένες διαφορές στα ΕΜΜ της ποικιλότητας μικροβιώματος κατά αριθμό προηγούμενων μαθημάτων αντιβιοτικών. Τα αστέρια δείχνουν σημαντικές διαφορές (FDR < 5%). γ, οι συσχετίσεις μεταξύ της χρήσης αντιβιοτικών τα 8 χρόνια πριν από τη δειγματοληψία κοπράνων και της ποικιλότητας των ειδών μικροβιώματος του εντέρου διερευνήθηκαν χρησιμοποιώντας μοντέλα παλινδρόμησης προσαρμοσμένα για τις ίδιες συμμεταβλητές όπως παραπάνω, σε τρεις κοόρτες (SCAPIS, SIMPLER, MOS, σύνολο n = 14.974), ακολουθούμενες από μετα-αναλύσεις του συντελεστή παλινδρόμησης. Ο άξονας x και τα διαμάντια εμφανίζουν τους μετα-αναλυμένους συντελεστές παλινδρόμησης. Οι γραμμές σφαλμάτων αντιπροσωπεύουν 95% διαστήματα εμπιστοσύνης. Τα συμπληρωμένα σύμβολα υποδεικνύουν στατιστικά σημαντικές συσχετίσεις (FDR < 5%). Εμφανίζονται αντιβιοτικά με τουλάχιστον μία τέτοια συσχέτιση.

aMicrobiome diversity measures (Shannon Index, species richness and inverse (Inv.) Simpson Index) for each additional course of any antibiotic 4–8 years, 1–4 years and <1 year before stool sampling. Estimated marginal means (EMMs) of diversity were obtained using regression models, with antibiotic exposure modeled using restricted cubic lines and adjusting for age, sex, smoking, education, country of birth, panel analysis by site, BMI, Charlson Comorbidity Index, polypharmacy and use of antipsychotic PPIs (n = 14,974). Squares represent EMMs and block 95% confidence intervals. siPairwise differences in EMMs of microbiome diversity by number of previous antibiotic courses. Stars indicate significant differences (FDR < 5%). doAssociations between antibiotic use in the 8 years prior to stool sampling and gut microbiome species diversity were explored using regression models adjusted for the same covariates as above, in three cohorts (SCAPIS, SIMPLER, MOS, total n = 14,974), followed by regression coefficient meta-analyses. The x-axis and diamonds show the post-analyzed regression coefficients. Error bars represent 95% confidence intervals. Filled symbols indicate statistically significant associations (FDR < 5%). Antibiotics with at least one such association appear.

Implications for antibiotic stewardship and future research

The findings suggest that some antibiotics can have long-lasting effects on the gut microbiome, persisting for more than four years. These results support more judicious antibiotic prescribing and management strategies that minimize microbiome disruption.

However, the study remains observational and cannot prove causality. Further research is needed to understand long-term health consequences, including links to chronic disease. The findings may not generalize beyond outpatient clinics in Sweden and may underestimate overall antibiotic exposure due to a lack of hospital or international prescribing data.

Journal Reference:

  • Baldanzi, G. et al. (2026). Antibiotic use and gut microbiome composition linked from individual-level prescription data of 14,979 subjects. Nature Medicine, 1-11. DOI: 10.1038/s41591-026-04284-y, https://www.nature.com/articles/s41591-026-04284-y
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