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Comment
. 2023 Jul;72(7):1431-1433.
doi: 10.1136/gutjnl-2022-328034. Epub 2022 Sep 1.

Ageing trajectory of the gut microbiota is associated with metabolic diseases in a chronological age-dependent manner

JingXiang Fu #  1 , Wen Qiu #  1 , Huimin Zheng  1 , Cancan Qi  1 , Shixian Hu  2 , Wei Wu  3 , Huidi Wang  1 , Guangyan Wu  1 , Peihua Cao  4   5 , Zhenchao Ma  6 , Chao Zheng  6 , Wen-Jun Ma  7 , Hong-Wei Zhou  1   8 , Yan He  9   8
Affiliations
Comment

Ageing trajectory of the gut microbiota is associated with metabolic diseases in a chronological age-dependent manner

JingXiang Fu et al. Gut. 2023 Jul.
No abstract available

Keywords: AGEING; COLONIC MICROFLORA; GLUCOSE METABOLISM; LIPID METABOLISM.

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Conflict of interest statement

Competing interests: None declared.

Figures

Figure 1
Figure 1
Gut microbiome ageing patterns in participants with metabolic diseases and their healthy counterparts. (A) Three different patterns of ageing trajectories of the gut microbiota. (B–D) Gut microbiota ageing trajectory in patients with hypertension, diabetes and obesity versus healthy individuals. The random forest model was trained with the microbiota features of healthy individuals and then applied to predict the microbiota age of participants with hypertension, diabetes and obesity in relation to their chronological their age separately.
Figure 2
Figure 2
Significant intersecting trajectories of taxonomic relative abundances in healthy and hypertensive participants. (A) Heatmap of the top 20 important amplicon sequence variant from the random forest regression model plotted against chronological age in healthy and hypertensive individuals. Significant intersecting patterns of the relative abundances of (B) seq93_Clostridium and (C) seq15333_Parabacteroides distasonis in healthy individuals and hypertensive participants. The interaction p indicates the significance of interaction term in the multivariable linear regression model.
See this image and copyright information in PMC

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References

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