Your gut bacteria shape your health from childhood to old age, study reveals

Scientists uncover how your gut bacteria evolve over time—impacting weight, diabetes, and heart health—offering new insights into preventing metabolic diseases.

Study: Association between gut microbiome profiles and host metabolic health across the life course: a population-based study. Image Credit: Tatiana Shepeleva / Shutterstock

Did you know that over 1 billion people worldwide suffer from metabolic disorders like obesity and type 2 diabetes mellitus (T2DM)? These conditions are major contributors to global health burdens, increasing the risk of cardiovascular diseases and reducing life expectancy.

The gut microbiome plays a crucial role in metabolic health, yet its influence evolves from infancy to old age, shaped by diet, lifestyle, and genetics.

While previous studies focus on specific age groups, understanding these associations across the lifespan is essential for targeted preventive strategies. Further research is needed to determine the long-term metabolic implications of microbiome changes and potential interventions. However, the ability to translate these findings into clinical recommendations is limited by differences in study methodologies and the dynamic nature of gut microbiome composition over time.

About the Study

In a recent study published in The Lancet Regional Health – Europe, a population-based study was conducted using three Dutch cohorts representing different life stages: pre-adolescents from the Generation R Study (GenR) (mean age 9.8 years, n = 1488), older adults from the Rotterdam Study (RS) (mean age 62.7 years, n = 1265), and an adult validation cohort from the Lifelines-DEEP Study (LLD) (mean age 45.0 years, n = 1117).

Stool samples were collected, and bacterial deoxyribonucleic acid (DNA) was extracted and sequenced using 16S ribosomal ribonucleic acid (rRNA) gene sequencing. Microbiome clustering was performed using the K-Means algorithm to identify patterns associated with metabolic health.

Anthropometric measurements, blood biomarkers (glucose, insulin, triglycerides, cholesterol), and lifestyle factors (diet, physical activity, smoking) were assessed. Logistic regression models were used to analyze the association between microbiome clusters and metabolic health, adjusting for confounders such as age, sex, and medication use.

In the RS, a longitudinal follow-up (median 6.5 years) was conducted to assess the relationship between microbiome clusters and atherosclerotic cardiovascular disease (ASCVD) incidence. Multiple imputation was used for missing data. Statistical analyses were performed using R software. Ethical approval was obtained, and participants provided written informed consent.

It is important to note that dietary data for some participants were collected years before stool sampling, which could affect the interpretation of microbiome-diet interactions.

Study Results

Two distinct microbiome clusters, labeled Cluster U (unhealthy) and Cluster H (healthy), were identified in each cohort. Cluster U was characterized by lower microbial diversity and an increased abundance of Streptococcus and Fusicatenibacter, whereas Cluster H exhibited higher diversity with greater levels of Christensenellaceae_R-7_group and Prevotella_9.

In pre-adolescents, those assigned to Cluster U had higher body fat percentage, triglyceride levels, and C-reactive protein (CRP), indicating a higher inflammatory state. In older adults, Cluster U was associated with increased waist-to-hip ratio (WHR), insulin resistance, and hypertension.

Similar patterns were observed in the LLD validation cohort, where individuals in Cluster U had higher obesity prevalence and lower high-density lipoprotein cholesterol (HDL-C) levels.

Logistic regression analysis showed that individuals in Cluster U had between 1.10 and 1.65 times higher odds of being metabolically unhealthy compared to those in Cluster H. This association was strongest in older adults (OR = 1.61, 95% CI: 1.29–2.01), suggesting that gut microbiome composition becomes a more significant determinant of metabolic health with age.

A key finding was the link between microbiome clusters and future cardiovascular risk. In the RS, individuals in Cluster U had a significantly higher mean 5-year ASCVD risk (mean 0.059 ± 0.071) compared to those in Cluster H (mean 0.047 ± 0.042, p < 0.001). However, survival analysis did not find this difference to be statistically significant (hazard ratio [HR] = 1.52, 95% CI: 0.83–2.80, p > 0.05), meaning the observed trend requires further investigation in larger studies.

Factors influencing microbiome cluster assignment included socioeconomic status (SES), smoking, and proton pump inhibitor (PPI) use. Lower maternal education levels were linked to an unhealthy microbiome in children, while lower personal education levels influenced clustering in adults. Importantly, while certain bacterial taxa were associated with metabolic health across cohorts, the overall microbiome composition showed some variability between groups, likely due to differences in age, lifestyle, and sequencing methodologies.

These findings have far-reaching implications for individuals and communities. A deeper understanding of microbiome-driven metabolic health could lead to personalized dietary and lifestyle recommendations to prevent obesity and metabolic disorders. However, due to the complexity of gut microbiome interactions, translating these findings into clinical interventions remains challenging.

On a global scale, addressing gut microbiome imbalances could significantly reduce healthcare costs and disease burden.

Study Limitations

This study provides valuable evidence of a life-course relationship between gut microbiome composition and metabolic health. However, some limitations should be considered:

• The study used 16S rRNA sequencing, which has limited taxonomic resolution, meaning it cannot distinguish specific bacterial species or functional traits.
• While ASCVD risk was assessed, the follow-up period (6.5 years) was relatively short, and the association between microbiome clusters and cardiovascular outcomes did not reach statistical significance.
• The study population consisted mainly of Dutch individuals, which may limit generalizability to more ethnically diverse populations.
• Dietary data were collected years before stool samples, which may affect conclusions regarding diet-microbiome interactions.

Conclusions

This study provides evidence of a life-course relationship between gut microbiome composition and metabolic health. Individuals with an unhealthy microbiome profile had higher body fat, insulin resistance, and triglyceride levels, and they were at a greater risk of developing cardiovascular disease.

These associations were stronger in older adults, suggesting that gut microbiome diversity plays an increasing role in metabolic health over time. Given that gut microbiome composition is modifiable through diet and lifestyle, early-life interventions targeting microbial health may provide a unique opportunity to prevent metabolic disorders later in life.

However, further research is needed to determine whether microbiome-targeted interventions, such as probiotics, prebiotics, or dietary modifications, can have a meaningful impact on long-term metabolic health outcomes.

Final Thoughts

With growing evidence supporting the gut microbiome’s role in metabolic health, scientists continue to explore its potential as a biomarker for disease prediction and a target for personalized interventions. While findings from this study highlight strong associations, translating microbiome science into everyday healthcare still requires further clinical validation and understanding of the underlying mechanisms.