ArticleFrontiers in microbiology2021
Compositional Data Analysis of Periodontal Disease Microbial Communities.
Article in Frontiers in microbiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.
What it found
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
16 citing papers in PubMed, 1 synthesis or guideline pooled it, 23 citations in OpenAlex.
- Microbial Markers for Diagnosis and Risk Assessment for Periodontal Diseases: A Systematic Literature Search and Narrative Synthesis.Journal of clinical periodontology · 2025Pooled it
- [The Oral Microbiome: Maintenance of Homeostasis, Disease Associations, and Mechanisms of Pathogenesis].Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition · 2026Review
- Dysbiotic shift in the oral microbiota of patients with Alzheimer's disease compared to their healthy life partners-a combinatorial approach and a paired study design.Alzheimer's research & therapy · 2026Article
- Molecular cytokine-dependent mechanisms of periodontitis pathogenesis and the potential for pharmacological IL-1 modulation in disease treatment.Frontiers in dental medicine · 2026Review
- Effects of 0.01 mM strontium on human periodontal ligament stem cell osteogenic differentiation via the Wnt/The Journal of international medical research · 2025Article
- In Vitro Infection of Human Macrophages withInternational journal of molecular sciences · 2025Article
- Microbiological and molecular aspects of periodontitis pathogenesis: an infection-induced inflammatory condition.Frontiers in cellular and infection microbiology · 2025Review
- Effect of Dietary Composite Probiotic Supplementation on the Microbiota of Different Oral Sites in Cats.Veterinary sciences · 2024Article
- Article
- Proportion-based normalizations outperform compositional data transformations in machine learning applications.Microbiome · 2024Article
- Data-driven mathematical and visualization approaches for removing rare features for Compositional Data Analysis (CoDA).NAR genomics and bioinformatics · 2024Article
- Astragalus-cultivated soil was a suitable bed soil for nurturing Angelica sinensis seedlings from the rhizosphere microbiome perspective.Scientific reports · 2023Article
- Ecological shifts of salivary microbiota associated with metabolic-associated fatty liver disease.Frontiers in cellular and infection microbiology · 2023Article
- Features of the oral microbiome in Japanese elderly people with 20 or more teeth and a non-severe periodontal condition during periodontal maintenance treatment: A cross-sectional study.Frontiers in cellular and infection microbiology · 2022Article
- Macroscopic Changes in Oral Mucosa and Hygiene Indicators in Smokers.Current health sciences journalArticle
- Oral Microbiome and Cognition Among Black Cancer Caregivers.Nursing researchArticle
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Periodontal disease (PD) is a chronic, progressive polymicrobial disease that induces a strong host immune response. Culture-independent methods, such as next-generation sequencing (NGS) of bacteria 16S amplicon and shotgun metagenomic libraries, have greatly expanded our understanding of PD biodiversity, identified novel PD microbial associations, and shown that PD biodiversity increases with pocket depth. NGS studies have also found PD communities to be highly host-specific in terms of both biodiversity and the response of microbial communities to periodontal treatment. As with most microbiome work, the majority of PD microbiome studies use standard data normalization procedures that do not account for the compositional nature of NGS microbiome data. Here, we apply recently developed compositional data analysis (CoDA) approaches and software tools to reanalyze multiomics (16S, metagenomics, and metabolomics) data generated from previously published periodontal disease studies. CoDA methods, such as centered log-ratio (clr) transformation, compensate for the compositional nature of these data, which can not only remove spurious correlations but also allows for the identification of novel associations between microbial features and disease conditions. We validated many of the studies' original findings, but also identified new features associated with periodontal disease, including the genera
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.