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Can the Salivary Microbiome Predict Cardiovascular Diseases? Lessons Learned From the Qatari Population

journal contribution
submitted on 2024-07-07, 07:35 and posted on 2024-07-07, 07:36 authored by Selvasankar Murugesan, Mohammed Elanbari, Dhinoth Kumar Bangarusamy, Annalisa Terranegra, Souhaila Al Khodor

Background

Many studies have linked dysbiosis of the gut microbiome to the development of cardiovascular diseases (CVD). However, studies assessing the association between the salivary microbiome and CVD risk on a large cohort remain sparse. This study aims to identify whether a predictive salivary microbiome signature is associated with a high risk of developing CVD in the Qatari population.

Methods

Saliva samples from 2,974 Qatar Genome Project (QGP) participants were collected from Qatar Biobank (QBB). Based on the CVD score, subjects were classified into low-risk (LR < 10) (n = 2491), moderate-risk (MR = 10–20) (n = 320) and high-risk (HR > 30) (n = 163). To assess the salivary microbiome (SM) composition, 16S-rDNA libraries were sequenced and analyzed using QIIME-pipeline. Machine Learning (ML) strategies were used to identify SM-based predictors of CVD risk.

Results

Firmicutes and Bacteroidetes were the predominant phyla among all the subjects included. Linear Discriminant Analysis Effect Size (LEfSe) analysis revealed that Clostridiaceae and Capnocytophaga were the most significantly abundant genera in the LR group, while Lactobacillus and Rothia were significantly abundant in the HR group. ML based prediction models revealed that Desulfobulbus, Prevotella, and Tissierellaceae were the common predictors of increased risk to CVD.

Conclusion

This study identified significant differences in the SM composition in HR and LR CVD subjects. This is the first study to apply ML-based prediction modeling using the SM to predict CVD in an Arab population. More studies are required to better understand the mechanisms of how those microbes contribute to CVD.

Other Information

Published in: Frontiers in Microbiology
License: https://creativecommons.org/licenses/by/4.0/
See article on publisher's website: https://dx.doi.org/10.3389/fmicb.2021.772736

Funding

Qatar National Research Fund (PPM2-0216-170012), Saliva diagnostics to pave the way towards personalized medicine.

Qatar Genome Program (N/A)

History

Language

  • English

Publisher

Frontiers

Publication Year

  • 2021

License statement

This Item is licensed under the Creative Commons Attribution 4.0 International License.

Institution affiliated with

  • Sidra Medicine
  • Clinical Research Centre - Sidra Medicine

Geographic coverage

Qatar

Related Datasets

Murugesan, S., Elanbari, M., Bangarusamy, D. K., Terranegra, A., & Al Khodor, S. (2021). Can the Salivary Microbiome Predict Cardiovascular Diseases? Lessons Learned From the Qatari Population. Frontiers in Microbiology, 12. https://doi.org/10.3389/fmicb.2021.772736. National Institutes of Health : National Center for Biotechnology Information : Gene : Bioproject : Qatari salivary microbiome : Accession: PRJNA781451. Last modified 2021. https://www.ncbi.nlm.nih.gov/gene/?term=PRJNA781451

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