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Volume 48 Issue 1
Jan.  2021
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Article Contents

The oral microbiome of pregnant women facilitates gestational diabetes discrimination

doi: 10.1016/j.jgg.2020.11.006
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  • The oral microbiota plays an important role in the development of various diseases, whereas its association with gestational diabetes mellitus (GDM) remains largely unclear. The aim of this study is to identify biomarkers from the oral microbiota of GDM patients by analyzing the microbiome of the saliva and dental plaque samples of 111 pregnant women. We find that the microbiota of both types of oral samples in GDM patients exhibits differences and significantly varies from that of patients with periodontitis or dental caries. Using bacterial biomarkers from the oral microbiota, GDM classification models based on support vector machine and random forest algorithms are constructed. The area under curve (AUC) value of the classification model constructed by combination of Lautropia and Neisseria in dental plaque and Streptococcus in saliva reaches 0.83, and the value achieves a maximum value of 0.89 by adding clinical features. These findings suggest that certain bacteria in either saliva or dental plaque can effectively distinguish women with GDM from healthy pregnant women, which provides evidence of oral microbiome as an informative source for developing noninvasive biomarkers of GDM.
  • These authors contribute equally to this work.
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  • [1]
    Acuna, J., Cohavy, O., Solt, I., Reeder, J., Kim, M., Lebovics, I., Paster, B., Knight, R., Rotmensch, S., 2011. Preliminary observations on the microbial phylogeny of the oral, vaginal, and rectal microbiome in gestational diabetes and healthy pregnancies. Am. J. Obstet. Gynecol. 204, S109-S110.
    [2]
    Artzi, N. S., Shilo, S., Hadar, E., Rossman, H., Barbash-Hazan, S., Ben-Haroush, A., Balicer, R. D., Feldman, B., Wiznitzer, A., Segal, E., 2020. Prediction of gestational diabetes based on nationwide electronic health records. Nat. Med. 26(1), 71-76.
    [3]
    Belstrom, D., Paster, B. J., Fiehn, N. E., Bardow, A., Holmstrup, P., 2016. Salivary bacterial fingerprints of established oral disease revealed by the Human Oral Microbe Identification using Next Generation Sequencing (HOMINGS) technique. J. Oral Microbiol. 8, 30170.
    [4]
    Buchanan, T. A., Xiang, A. H., Page, K. A., 2012. Gestational diabetes mellitus: risks and management during and after pregnancy. Nat. Rev. Endocrinol. 8, 639-649.
    [5]
    Camelo-Castillo, A. J., Mira, A., Pico, A., Nibali, L., Henderson, B., Donos, N., Tomas, I., 2015. Subgingival microbiota in health compared to periodontitis and the influence of smoking. Front. Microbiol. 6, 119.
    [6]
    Cheung, N. W., Byth, K., 2003. Population health significance of gestational diabetes. Diabetes Care 26, 2005-2009.
    [7]
    Crusell, M. K. W., Brink, L. R., Nielsen, T., Allin, K. H., Hansen, T., Damm, P., Lauenborg, J., Hansen, T. H., Pedersen, O., 2020. Gestational diabetes and the human salivary microbiota: a longitudinal study during pregnancy and postpartum. BMC Pregnancy Childb. 20, 69.
    [8]
    Crusell, M. K. W., Hansen, T. H., Nielsen, T., Allin, K. H., Ruhlemann, M. C., Damm, P., Vestergaard, H., Rorbye, C., Jorgensen, N. R., Christiansen, O. B., Heinsen, F. A., Franke, A., Hansen, T., Lauenborg, J., Pedersen, O., 2018. Gestational diabetes is associated with change in the gut microbiota composition in third trimester of pregnancy and postpartum. Microbiome 6, 89.
    [9]
    Damm, P., Mathiesen, E. R., 2015. Diabetes: therapy for gestational diabetes mellitus--time for a change? Nat. Rev. Endocrinol. 11, 327-328.
    [10]
    Damm, P., Houshmand-Oeregaard, A., Kelstrup, L., Lauenborg, Jeannet., Mathiesen, E. R., Clausen, T. D., 2016. Gestational diabetes mellitus and long-term consequences for mother and offspring: a view from Denmark. Diabetologia 59, 1396-1399.
    [11]
    Dzunkova, M., Martinez-Martinez, D., Gardlik, R., Behuliak, M., Jansakova, K., Jimenez, N., Vazquez-Castellanos, J. F., Marti, J. M., D’Auria, G., Bandara, Hmhn., Latorre, A., Celec, P., Moya, A., 2018. Oxidative stress in the oral cavity is driven by individual-specific bacterial communities. NPJ Biofilms Microbi. 4, 29.
    [12]
    Farrell, J. J., Zhang, L., Zhou, H., Chia, D., Elashoff, D., Akin, D., Paster, B. J., Joshipura, K., Wong, D. T., 2012. Variations of oral microbiota are associated with pancreatic diseases including pancreatic cancer. Gut 61, 582-588.
    [13]
    Graziani, F., Gennai, S., Solini, A., Petrini, M., 2018. A systematic review and meta-analysis of epidemiologic observational evidence on the effect of periodontitis on diabetes An update of the EFP-AAP review. J. Clin. Periodontol. 45, 167-187.
    [14]
    Gumus, P., Ozcaka, O., Ceyhan-Ozturk, B., Akcali, A., Lappin, D. F., Buduneli, N., 2015. Evaluation of biochemical parameters and local and systemic levels of osteoactive and B-cell stimulatory factors in gestational diabetes in the presence or absence of gingivitis. J. Periodontol. 86, 387-397.
    [15]
    Hasan, S., Aho, V., Pereira, P., Paulin, L., Koivusalo, S. B., Auvinen, P., Eriksson, J. G., 2018. Gut microbiome in gestational diabetes: a cross-sectional study of mothers and offspring 5 years postpartum. Acta. Obstet. Gynecol. Scand. 97, 38-46.
    [16]
    Huang, S., Li, R., Zeng, X., He, T., Zhao, H., Chang, A., Bo, C., Chen, J., Yang, F., Knight, R., Liu, J., Davis, C., Xu, J., 2014. Predictive modeling of gingivitis severity and susceptibility via oral microbiota. ISME J. 8, 1768-1780.
    [17]
    Kim, B. S., Han, D. H., Lee, H., Oh, B., 2018. Association of salivary microbiota with dental caries incidence with dentine involvement after 4 years. J. Microbiol. Biotechnol. 28, 454-464.
    [18]
    Kinross, J. M., Darzi, A. W., Nicholson J. K., 2011. Gut microbiome-host interactions in health and disease. Genome Med. 3, 14.
    [19]
    Kolenbrander, P. E., Andersen, R. N., Blehert, D. S., Egland, P. G., Foster, J. S., Palmer, R. J., Jr., 2002. Communication among oral bacteria. Microbiol. Mol. Biol. Rev. 66, 486-505, table of contents.
    [20]
    Koopman, J. E., Roling, W. F., Buijs, M. J., Sissons, C. H., ten Cate, J. M., Keijser, B. J., Crielaard, W., Zaura, E., 2015. Stability and resilience of oral microcosms toward acidification and Candida outgrowth by arginine supplementation. Microb. Ecol. 69, 422-433.
    [21]
    Lloyd-Price, J., Abu-Ali, G., Huttenhower, C., 2016. The healthy human microbiome. Genome Med. 8, 51.
    [22]
    Martinez, K. B., Leone, V., Chang, E. B., 2017. Microbial metabolites in health and disease: navigating the unknown in search of function. J. Biol. Chem. 292, 8553-8559.
    [23]
    Nassr, A. A., Shazly, S. A., Trinidad, M. C., El-Nashar, S. A., Marroquin, A. M., Brost, B. C., 2018. Body fat index: a novel alternative to body mass index for prediction of gestational diabetes and hypertensive disorders in pregnancy. Eur. J. Obstet. Gynecol. Reprod. Biol. 228, 243-248.
    [24]
    Ng, S. K., Hamilton, I. R., 1971. Lactate metabolism by Veillonella parvula. J. Bacteriol. 105, 999-1005.
    [25]
    Qin, N., Yang, F., Li, A., Prifti, E., Chen, Y., Shao, L., Guo, J., Le Chatelier, E., Yao, J., Wu, L., Zhou, J., Ni, S., Liu, L., Pons, N., Batto, J. M., Kennedy, S. P., Leonard, P., Yuan, C., Ding, W., Chen, Y., Hu, X., Zheng, B., Qian, G., Xu, W., Ehrlich, S. D., Zheng, S., Li, L., 2014. Alterations of the human gut microbiome in liver cirrhosis. Nature 513, 59-64.
    [26]
    Seraphim, A. P., Chiba, F. Y., Pereira, R. F., Mattera, M. S., Moimaz, S. A., Sumida, D. H., 2016. Relationship among periodontal disease, insulin resistance, salivary cortisol, and stress levels during pregnancy. Braz. Dent. J. 27, 123-127.
    [27]
    Takahashi, N., Yamada, T., 1999. Glucose and lactate metabolism by Actinomyces naeslundii. Crit. Rev. Oral. Biol. Med. 10, 487-503.
    [28]
    Teng, F., Yang, F., Huang, S., Bo, C., Xu, Z. Z., Amir, A., Knight, R., Ling, J., Xu, J., 2015. Prediction of early childhood caries via spatial-temporal variations of oral microbiota. Cell Host Microbe 18, 296-306.
    [29]
    Thomas, A. M., Manghi, P., Asnicar, F., Pasolli, E., Armanini, F., Zolfo, M., Beghini, F., Manara, S., Karcher, N., Pozzi, C., Gandini, S., Serrano, D., Tarallo, S., Francavilla, A., Gallo, G., Trompetto, M., Ferrero, G., Mizutani, S., Shiroma, H., Shiba, S., Shibata, T., Yachida, S., Yamada, T., Wirbel, J., Schrotz-King, P., Ulrich, C. M., Brenner, H., Arumugam, M., Bork, P., Zeller, G., Cordero, F, Dias-Neto, E., Setubal, J. C., Tett, A., Pardini, B., Rescigno, M., Waldron, L., Naccarati, A., Segata, N., 2019. Metagenomic analysis of colorectal cancer datasets identifies cross-cohort microbial diagnostic signatures and a link with choline degradation. Nat. Med. 25, 667-678.
    [30]
    Wang, J., Jia, Z., Zhang, B., Peng, L., Zhao, F., 2019. Tracing the accumulation of in vivo human oral microbiota elucidates microbial community dynamics at the gateway to the GI tract. Gut 69, 1355-1356.
    [31]
    Wang, J., Qi, J., Zhao, H., He, S., Zhang, Y., Wei, S., Zhao, F., 2013. Metagenomic sequencing reveals microbiota and its functional potential associated with periodontal disease. Sci. Rep. 3, 1843.
    [32]
    Wang, J., Zheng, J., Shi, W., Du, N., Xu, X., Zhang, Y., Ji, P., Zhang, F., Jia, Z., Wang, Y., Zheng, Z., Zhang, H., Zhao, F., 2018. Dysbiosis of maternal and neonatal microbiota associated with gestational diabetes mellitus. Gut 67, 1614-1625.
    [33]
    Weinert, L. S., 2010. International association of diabetes and pregnancy study groups recommendations on the diagnosis and classification of hyperglycemia in pregnancy: comment to the international association of diabetes and pregnancy study groups consensus panel. Diabetes Care 33, e97.
    [34]
    Xiao, C., Ran, S., Huang, Z., Liang, J., 2016. Bacterial diversity and community structure of supragingival plaques in adults with dental health or caries revealed by 16S pyrosequencing. Front. Microbiol. 7, 1145.
    [35]
    Zakrzewski, M., Proietti, C., Ellis, J. J., Hasan, S., Brion, M. J., Berger, B., Krause, L., 2017. Calypso: a user-friendly web-server for mining and visualizing microbiome-environment interactions. Bioinformatics 33, 782-783.
    [36]
    Zheng, J., Xiao, X., Zhang, Q., Mao, L., Yu, M., Xu, J., Wang, T., 2017. The placental microbiota is altered among subjects with gestational diabetes mellitus: a pilot study. Front. Physiol. 8, 675.
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