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Meta-Analysis
. 2024 Oct 11;16(20):3440.
doi: 10.3390/nu16203440.

Akkermansia muciniphila for the Prevention of Type 2 Diabetes and Obesity: A Meta-Analysis of Animal Studies

Ethan Liu  1 , Xiangming Ji  2 , Kequan Zhou  1
Affiliations
Meta-Analysis

Akkermansia muciniphila for the Prevention of Type 2 Diabetes and Obesity: A Meta-Analysis of Animal Studies

Ethan Liu et al. Nutrients. .

Abstract

Background: More than half of the states in the U.S. report that over 30% of adults are obese. Obesity increases the risk of many chronic diseases, including type 2 diabetes, hypertension, and cardiovascular disease, and can even reduce one's lifespan. Similarly, the prevalence of type 2 diabetes follows a comparable trend. As a result, researchers are striving to find solutions to reduce obesity rates, with a particular focus on gut health, which has been previously linked to both obesity and type 2 diabetes. Recent studies suggest that Akkermansia muciniphila (Akk) may have a positive probiotic effect on preventing the onset of type 2 diabetes and obesity.

Methods: We conducted a quantitative meta-analysis of 15 qualified animal studies investigating the effects of Akk administration as a probiotic.

Results: The statistical analyses showed that Akk administration significantly reduced body weight gain by 10.4% and fasting blood glucose by 21.2%, while also significantly improving glucose tolerance by 22.1% and increasing blood insulin levels by 26.9%. However, our analysis revealed substantial heterogeneity between the control and experimental groups across all subgroups.

Conclusions: Overall, Akk appears to be effective at reducing the onset of type 2 diabetes and diet-induced obesity. Long-term studies with larger sample sizes are needed to confirm these beneficial effects, as the current animal studies were of short duration (less than 20 weeks).

Keywords: Akkermansia; animals; meta-analysis; obesity; probiotic; type 2 diabetes.

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Conflict of interest statement

The authors declare no conflicts of interest. The funders had no role in the design of this study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

Figures

Figure 1
Figure 1
Various pathways and models associated with A. muciniphila [7].
Figure 2
Figure 2
Selection of studies for the meta-analysis.
Figure 3
Figure 3
Analysis of experimental characteristics used in animal models for Akkermansia muciniphila studies. (A): Breakdown of diets used in animal studies. (B): Animal sexes used in mouse animal studies. (C): Evaluation of methodological quality score for animal studies (max score = 12). MQS, Methodological Quality Score.
Figure 4
Figure 4
Quantitative analysis of studies that assessed body weight using a random-effects meta-analysis. (A): Forest plot of studies investigating body weight effects (normalized mean difference ± 95% CI) [31,32,33,34,36,40,41,42,43]. Effect size estimates were heterogenous, likely owing to study design differences. (B): Funnel plot used to assess publication bias. These results suggest that the studies used in the meta-analysis had relatively low publication bias (i.e., the symmetric distribution of closed circles). (C): Baujat plot used to assess the studies that contributed most to heterogeneity. These results suggest that studies Chung et al. 2020 [33] and Wu et al. 2020 [41] likely had moderating variables that contributed the most to the heterogeneity.
Figure 5
Figure 5
Quantitative analysis of studies that assessed glucose tolerance using a random-effects meta-analysis. (A): Forest plot of studies investigating glucose tolerance (normalized mean difference ±95% CI) [31,33,34,36,37,38,39,40,41]. Effect size estimates were heterogenous, likely owing to study design differences. (B): Funnel plot used to assess publication bias. These results suggest that the studies used in the meta-analysis had relatively low publication bias. (C): Baujat plot used to assess the studies that contributed most to heterogeneity. These results suggest that the study Shin et al. 2014 [38] likely had moderating variables that contributed the most to the heterogeneity.
Figure 5
Figure 5
Quantitative analysis of studies that assessed glucose tolerance using a random-effects meta-analysis. (A): Forest plot of studies investigating glucose tolerance (normalized mean difference ±95% CI) [31,33,34,36,37,38,39,40,41]. Effect size estimates were heterogenous, likely owing to study design differences. (B): Funnel plot used to assess publication bias. These results suggest that the studies used in the meta-analysis had relatively low publication bias. (C): Baujat plot used to assess the studies that contributed most to heterogeneity. These results suggest that the study Shin et al. 2014 [38] likely had moderating variables that contributed the most to the heterogeneity.
Figure 6
Figure 6
Quantitative analysis of studies that assessed insulin hormone levels using a random-effects meta-analysis. (A): Forest plot of studies investigating insulin levels (normalized mean difference ±95% CI) [30,31,32,33,34,36,37,38,39,40,41,42,43]. Effect size estimates were very heterogenous, likely owing to study design differences and differences in probiotic duration. (B): Funnel plot used to assess publication bias. These results suggest that the studies used in the meta-analysis had relatively low publication bias. (C): Baujat plot used to assess the studies that contributed most to heterogeneity. These results suggest that studies Shin et al. 2014 [38], Song et al. 2016 [39], and Wang et al. 2023 [40] likely had moderating variables that contributed the most to the heterogeneity.
Figure 7
Figure 7
Quantitative analysis of studies that assessed fasting blood glucose using a random-effects meta-analysis. (A): Forest plot of studies investigating fasting blood glucose (normalized mean difference ± 95% CI) [30,33,34,37,38,40,41,42,43]. Effect size estimates were heterogenous, likely owing to study design differences. (B): Funnel plot used to assess publication bias. These results suggest that the studies used in the meta-analysis had relatively low publication bias. (C): Baujat plot used to assess the studies that contributed most to heterogeneity. These results suggest that studies Shin et al. 2014 [38], Wang et al. 2023 [40], and Wu et al. 2020 [41] likely had moderating variables that contributed the most to the heterogeneity.
Figure 7
Figure 7
Quantitative analysis of studies that assessed fasting blood glucose using a random-effects meta-analysis. (A): Forest plot of studies investigating fasting blood glucose (normalized mean difference ± 95% CI) [30,33,34,37,38,40,41,42,43]. Effect size estimates were heterogenous, likely owing to study design differences. (B): Funnel plot used to assess publication bias. These results suggest that the studies used in the meta-analysis had relatively low publication bias. (C): Baujat plot used to assess the studies that contributed most to heterogeneity. These results suggest that studies Shin et al. 2014 [38], Wang et al. 2023 [40], and Wu et al. 2020 [41] likely had moderating variables that contributed the most to the heterogeneity.
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References

    1. Bhupathiraju S.N., Hu F.B. Epidemiology of Obesity and Diabetes and Their Cardiovascular Complications. Circ. Res. 2016;118:1723–1735. doi: 10.1161/CIRCRESAHA.115.306825. - DOI - PMC - PubMed
    1. Xu Y., Wang N., Tan H.Y., Li S., Zhang C., Feng Y. Function of Akkermansia muciniphila in Obesity: Interactions With Lipid Metabolism, Immune Response and Gut Systems. Front. Microbiol. 2020;11:219. doi: 10.3389/fmicb.2020.00219. - DOI - PMC - PubMed
    1. Dao M.C., Everard A., Aron-Wisnewsky J., Sokolovska N., Prifti E., Verger E.O., Kayser B.D., Levenez F., Chilloux J., Hoyles L., et al. Akkermansia muciniphila and Improved Metabolic Health During a Dietary Intervention in Obesity: Relationship with Gut Microbiome Richness and Ecology. Gut. 2016;65:426–436. doi: 10.1136/gutjnl-2014-308778. - DOI - PubMed
    1. Arslanian S., Bacha F., Grey M., Marcus M.D., White N.H., Zeitler P. Evaluation and Management of Youth-Onset Type 2 Diabetes: A Position Statement by the American Diabetes Association. Diabetes Care. 2018;41:2648–2668. doi: 10.2337/dci18-0052. - DOI - PMC - PubMed
    1. Harsch I.A., Konturek P.C. The Role of Gut Microbiota in Obesity and Type 2 and Type 1 Diabetes Mellitus: New Insights into “Old” Diseases. Med. Sci. 2018;6:32. doi: 10.3390/medsci6020032. - DOI - PMC - PubMed

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