Gut Microbial Taxonomy and Its Role as a Biomarker in Aortic Diseases: A Systematic Review and Future Perspectives Article Swipe
Dina Neiroukh
,
Aida Hajdarpašić
,
Cagri Ayhan
,
Sherif Sultan
,
Osama Soliman
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.3390/jcm13226938
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.3390/jcm13226938
Background/Objectives: Evidence of the association between the gut microbiome and cardiovascular diseases has accumulated. An imbalance or dysbiosis of this system has been shown to play a role in the pathogenesis of cardiovascular events, including aortic diseases. We aimed to elucidate the findings of the gut microbial taxonomy associated with aortic diseases and their subtypes. Furthermore, we sought to investigate whether gut microbiome dysbiosis can be used as a biomarker for aortic disease detection and to identify which species can be disease-specific. Methods: A systematic search was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines for original research papers on gut microbiome composition in patients with aortic disease, using patients without aortic disease as the control (i.e., healthy controls). The databases PubMed, Scopus, Cochrane, and Web of Science were used by employing the medical subject headings (MeSH) terms “aortic diseases”, “microbiome”,” microbiota”, and ”taxa” before August 2024. We extracted the study characteristics, study population, and gut microbiome in aortic disease, including microbiota taxa diversity and abundance, regardless of taxa level. The National Institutes of Health (NIH) Quality Assessment Tool was used to assess study quality. Data were synthesized narratively to address the heterogeneity of the studies. Results: In this review, twelve studies that have identified gut microbial species and their potential impact on aortic disease pathogenesis were included. The studies showed the phyla dominance of Bacillota, Pseudomonadota, Actinomycetota, Bacteroidota, and Euryarchaeota in aortic disease patients. We also included the taxa sequencing methods and those used to extract the microorganisms. Aortic diseases were categorized into Takayasu’s arteritis, giant cell arteritis, aortic aneurysm, and aortic dissection. Aortic disease patients had a higher rate of dysbiosis when compared to the healthy control groups, with significantly different microbiome composition. Conclusions: Patients with aortic disease exhibit a distinct difference between their gut microbiota composition and that of the healthy controls, which suggests a potential biomarker role of gut dysbiosis. Further exploration of the microbiome and its metagenome interface can help identify its role in aortic disease pathogenesis in depth, generating future therapeutic options. However, a unified methodology is required to identify potential microbial biomarkers in cardiovascular and cardiometabolic diseases.
Related Topics
Concepts
Medicine
Biomarker
Biomarker discovery
Computational biology
Intensive care medicine
Proteomics
Genetics
Gene
Biology
Metadata
- Type
- review
- Language
- en
- Landing Page
- https://doi.org/10.3390/jcm13226938
- OA Status
- gold
- Cited By
- 3
- References
- 35
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4404527778
All OpenAlex metadata
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https://openalex.org/W4404527778Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3390/jcm13226938Digital Object Identifier
- Title
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Gut Microbial Taxonomy and Its Role as a Biomarker in Aortic Diseases: A Systematic Review and Future PerspectivesWork title
- Type
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reviewOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-11-18Full publication date if available
- Authors
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Dina Neiroukh, Aida Hajdarpašić, Cagri Ayhan, Sherif Sultan, Osama SolimanList of authors in order
- Landing page
-
https://doi.org/10.3390/jcm13226938Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
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goldOpen access status per OpenAlex
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https://doi.org/10.3390/jcm13226938Direct OA link when available
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Medicine, Biomarker, Biomarker discovery, Computational biology, Intensive care medicine, Proteomics, Genetics, Gene, BiologyTop concepts (fields/topics) attached by OpenAlex
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3Total citation count in OpenAlex
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2025: 3Per-year citation counts (last 5 years)
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