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Meta-Analysis
. 2022 Aug 23;23(1):214.
doi: 10.1186/s12931-022-02132-4.

The respiratory microbiota alpha-diversity in chronic lung diseases: first systematic review and meta-analysis

Marta Avalos-Fernandez  1   2 , Thibaud Alin #  3   4 , Clémence Métayer #  3   4 , Rodolphe Thiébaut  3   4   5 , Raphaël Enaud  6   7 , Laurence Delhaes  6   7   8
Affiliations
Meta-Analysis

The respiratory microbiota alpha-diversity in chronic lung diseases: first systematic review and meta-analysis

Marta Avalos-Fernandez et al. Respir Res. .

Abstract

Background: While there seems to be a consensus that a decrease in gut microbiome diversity is related to a decline in health status, the associations between respiratory microbiome diversity and chronic lung disease remain a matter of debate. We provide a systematic review and meta-analysis of studies examining lung microbiota alpha-diversity in patients with asthma, chronic obstructive pulmonary disease (COPD), cystic fibrosis (CF) or bronchiectasis (NCFB), in which a control group based on disease status or healthy subjects is provided for comparison.

Results: We reviewed 351 articles on title and abstract, of which 27 met our inclusion criteria for systematic review. Data from 24 of these studies were used in the meta-analysis. We observed a trend that CF patients have a less diverse respiratory microbiota than healthy individuals. However, substantial heterogeneity was present and detailed using random-effects models, which limits the comparison between studies.

Conclusions: Knowledge on respiratory microbiota is under construction, and for the moment, it seems that alpha-diversity measurements are not enough documented to fully understand the link between microbiota and health, excepted in CF context which represents the most studied chronic respiratory disease with consistent published data to link alpha-diversity and lung function. Whether differences in respiratory microbiota profiles have an impact on chronic respiratory disease symptoms and/or evolution deserves further exploration.

Keywords: Alpha-diversity; Asthma; Chronic obstructive respiratory disease; Chronic respiratory diseases; Cystic fibrosis; Factor Analysis of Mixed Data; Human lung bacteriome; Human lung microbiome; Meta-analysis; Non-cystic fibrosis bronchiectasis; Random-effects models.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
PRISMA flow diagram summarizing our search results and study selection for the systematic review and meta-analysis
Fig. 2
Fig. 2
Forest plot summarizing results from the random-effects meta-analysis model. A summary by type of sample, by disease and for all the studies is estimated by assuming the random effects model when data are available for at least two comparable studies. Values to the right of the vertical axis (positive values) indicate that the diversity of the control group (the healthiest group in each comparison) is greater than that of the case group. Conversely, values to the left of the vertical axis (negative values) indicate that the diversity of the control group is lower than that of the case group. When a confidence interval crosses the vertical axis, the standardized difference between the mean value of control diversity and the mean value of case diversity is not significant for the given study
Fig. 3
Fig. 3
FAMD biplot Vs. mean Shannon diversity differences between cases and controls. Dot sizes of studies (Byu17 [46] Car13 [27], Cob15 [45], Den16 [29], Ein16 [39], Erb11 [37], Fei17 [25], Gol13 [28], Hua20 [34], Kim17 [4], Lee18 [20], Li17 [32], Liu20 [31], Mar13 [33], Mil15 [41], Mun16 [35], Nar17 [44], Par14 [36], Ple19 [42], Pra12 [38], Sor20 [43], Sve17 [30], Wan20 [21]) are different depending on the disease. Color degree represents the sign (positive or negative) and the amount of the difference between mean diversity of cases and mean diversity of controls
See this image and copyright information in PMC

References

    1. Sokol H, Leducq V, Aschard H, Pham H, Jegou S, Landman C, Cohen D, Liguori G, Bourrier A, Nion-Larmurier I, Cosnes J, Seksik P, Langella P, Skurnik D, Richard M, Beaugerie L. Fungal microbiota dysbiosis in IBD. Gut. 2017;66(6):1039–1048. doi: 10.1136/gutjnl-2015-310746. - DOI - PMC - PubMed
    1. Ren Z, Li A, Jiang J, Zhou L, Yu Z, Lu H, Xie H, Chen X, Shao L, Zhang R, Xu S, Zhang H, Cui G, Chen X, Sun R, Wen H, Lerut J, Kan Q, Li L, Zheng S. Gut microbiome analysis as a tool towards targeted non-invasive biomarkers for early hepatocellular carcinoma. Gut. 2019;68(6):1014–1023. doi: 10.1136/gutjnl-2017-315084. - DOI - PMC - PubMed
    1. Agus A, Clément K, Sokol H. Gut microbiota-derived metabolites as central regulators in metabolic disorders. Gut. 2021;70(6):1174–1182. doi: 10.1136/gutjnl-2020-323071. - DOI - PMC - PubMed
    1. Kim B-R, Shin J, Guevarra RB, Lee JH, Kim DW, Seol K-H, Lee J-H, Kim HB, Isaacson RE. Deciphering diversity indices for a better understanding of microbial communities. J Microbiol Biotechnol. 2017;27(12):2089–2093. doi: 10.4014/jmb.1709.09027. - DOI - PubMed
    1. Whiteson K, Bailey B, Bergkessel M, Conrad D, Delhaes L, Felts B, Harris J, Hunter R, Lim Y, Maughan H, Quinn R, Salamon P, Sullivan J, Wagner B, Rainey P. The upper respiratory tract as a microbial source for pulmonary infections in cystic fibrosis. Parallels from island biogeography. Am J Respir Crit Care Med. 2014;189(11):1309–15. doi: 10.1164/rccm.201312-2129PP. - DOI - PMC - PubMed