June 6, 2024–In a groundbreaking study published today in Nature Medicine, researchers from the BGI Research Institute of Life Sciences and Ruijin Hospital affiliated with Shanghai Jiao Tong University School of Medicine have unveiled critical insights into how the gut microbiome influences cardiovascular disease (CVD) risk. The study, titled "Divergent Age-Associated and Metabolism-Associated Gut Microbiome Signatures Modulate Cardiovascular Disease Risk," explores the intricate relationships between aging, metabolic disorders, and gut microbiota, paving the way for potential new interventions in promoting health and longevity.

Key Findings from the Study

The extensive research analyzed data from nearly 20,000 participants, all aged 40 and above, over an average follow-up period of 11.1 years. By categorizing the participants into five distinct metabolic comorbidity subtypes (MCs) based on 21 precisely measured metabolic variables, researchers were able to draw significant correlations between these subtypes and cardiovascular disease risk. Additionally, metagenomic sequencing was performed on the gut microbiomes of 4,491 individuals, leading to the development of a novel health-aging indicator known as gut microbiome age (GM age).

Metabolic Comorbidity Subtypes and CVD Risk


a.In JD_2014 (N = 4,491), k-means-based unsupervised clustering was applied to 21 Z-score-transformed metabolic variables (including BMI, WC, SBP, DBP, FPG, PPG, HbA1c, Fins, Pins, HOMA-IR, TC, HDL-C, LDL-C, TG, ApoA-1, ApoB, ALT, AST, GGT, eGFR, and UA), revealing five robust MCs with distinctive subphenotypes. The heatmap displays the transformed values of 21 metabolic variables in all participants. b. Radar charts show the mean standardized Z-scores of metabolic variables of the JD_2014 cohort. Each MC exhibited a unique metabolic subphenotype, with MC1 characterized by a relatively healthy metabolic profile and other MCs by feature variables highlighted in colors. Colored feature variables for MCs2-5 were identified using the criteria of P < 0.05 and Cliff’s delta effect size>0.30 (two-sided Wilcoxon rank-sum test). c. Point plots show the average Jaccard similarity for the five MCs obtained using k-means clustering and random assignments in JD_2010, CM_2010, and JD_2014 (100 bootstrap resampling). d. Feature variables for each MC (MCs2-5 versus MC1) were identified using the criteria of P < 0.05 and Cliff’s delta effect size>0.3 (two-sided Wilcoxon rank-sum test) and are highlighted with an asterisk. e. The prevalence of metabolic disturbances closely aligned with the feature variables in each respective MC in JD_2010, CM_2010, and JD_2014.


Participants were grouped into five MCs:

1. Metabolically Healthy Group (MC1)

2. Low HDL-C and ApoA-1 Group (MC2)

3. High LDL-C, TC, and ApoB Group (MC3)

4. Obesity-Related Mixed Group (MC4)

5. High Blood Sugar Group (MC5)

The study revealed that participants in the Obesity-Related Mixed Group and High Blood Sugar Group had a 75% and 117% increased risk of developing cardiovascular diseases, respectively. These findings were validated in an independent cohort of 9,061 participants, reinforcing the predictive power of metabolic comorbidity subtypes in managing cardiovascular health risks.

Gut Microbiome and Aging

Further analysis of the gut microbiome data showed distinct associations between gut microbiota composition, age, and metabolic status. Specifically, Bacteroides were more abundant in younger individuals, while Prevotella were more common in older individuals. The study identified 55 age-associated gut microbiota species and used them to develop GM age, a new biological age indicator describing the gut microbiome's health and aging status.

Implications for Cardiovascular Health

In individuals over 60, a younger GM age correlated with a lower risk of cardiovascular diseases, regardless of actual age, sex, lifestyle, diet, and medication use. This novel biomarker holds significant potential for monitoring and managing CVD risk in the elderly with metabolic disorders.

Future Directions

This study underscores the crucial role of the gut microbiome in modulating cardiovascular disease risk through its interactions with aging and metabolic health. It opens new avenues for personalized health interventions aimed at adjusting the gut microbiome to maintain a younger GM age, thereby reducing CVD risk. Future research may focus on developing targeted strategies to modulate GM age, offering a novel approach to preventing cardiovascular diseases.

In the near future, personalized gut microbiome interventions could become a reality, promoting healthier aging and reducing cardiovascular disease risk, providing a new direction in preventive health care.


Wang, T., Shi, Z., Ren, H. et al. Divergent age-associated and metabolism-associated gut microbiome signatures modulate cardiovascular disease risk. Nat Med 30, 1722–1731 (2024).