Evidence map›Paper›PMID 36344584›Full record

ArticleScientific reports2022

Influential factors of saliva microbiota composition.

Philippa M Wells, Daniel D Sprockett, Ruth C E Bowyer, Yuko Kurushima, David A Relman, Frances M K Williams, Claire J Steves

Registry-linked trialAbstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06376656 (Successful Ageing), which is not on this map. Cited by 25 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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.

NCT06376656 naactive not recruitingnot on this map

Successful Ageing: Evidence-based Interventions to Delay Ageing-related Decline

TypeinterventionalSponsorSunway UniversityRan2022 to 2030Enrolled400ConditionsAging, Elderly, Cognitive Decline, Physical DeclineArmsCognitive stimulation, Physical activity
3 · Its place in the literature

Who cites it

25 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Positive Role of Saliva in the Oral Microbiome.Advances in experimental medicine and biology · 2025
    Review
  13. Frontiers in microbiology · 2025
    Article
  14. Acquisition of the Oral Microbiome.Advances in experimental medicine and biology · 2025
    Review
  15. Article
  16. Review
  17. Article
  18. Review
  19. Article
  20. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Philippa M WellsDepartment of Twin Research, St Thomas Hospital, King's College London, London, UK.
Daniel D SprockettDepartment of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA, 94305, USA.
Ruth C E BowyerDepartment of Twin Research, St Thomas Hospital, King's College London, London, UK.
Yuko KurushimaDepartment of Twin Research, St Thomas Hospital, King's College London, London, UK.
David A RelmanDepartment of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA, 94305, USA.
Frances M K WilliamsDepartment of Twin Research, St Thomas Hospital, King's College London, London, UK.
Claire J StevesDepartment of Twin Research, St Thomas Hospital, King's College London, London, UK. claire.j.steves@kcl.ac.uk.

Funding

British Heart FoundationMedical Research Council MR/M016560/1Medical Research Council MR/N01183X/1Versus Arthritis 21227Wellcome Trust 212904/Z/18/ZWellcome Trust WT081878MA
6 · The paper itself

Abstract

The oral microbiota is emerging as an influential factor of host physiology and disease state. Factors influencing oral microbiota composition have not been well characterised. In particular, there is a lack of population-based studies. We undertook a large hypothesis-free study of the saliva microbiota, considering potential influential factors of host health (frailty; diet; periodontal disease), demographics (age; sex; BMI) and sample processing (storage time), in a sample (n = 679) of the TwinsUK cohort of adult twins. Alpha and beta diversity of the saliva microbiota was associated most strongly with frailty (alpha diversity: β = -0.16, Q = 0.003, Observed; β = -0.16, Q = 0.002, Shannon; β = -0.16, Q = 0.003, Simpson; Beta diversity: Q = 0.002, Bray Curtis dissimilarity) and age (alpha diversity: β = 0.15, Q = 0.006, Shannon; β = 0.12, Q = 0.003, Simpson; beta diversity: Q = 0.002, Bray Curtis dissimilarity; Q = 0.032, Weighted UniFrac) in multivariate models including age, frailty, sex, BMI, frailty and diet, and adjustment for multiple testing. Those with a more advanced age were more likely to be dissimilar in the saliva microbiota composition than younger participants (P = 5.125e-06, ANOVA). In subsample analyses, including consideration of periodontal disease (total n = 138, periodontal disease n = 66), the association with frailty remained for alpha diversity (Q = 0.002, Observed ASVs; Q = 0.04 Shannon Index), but not beta diversity, whilst age was not demonstrated to associate with alpha or beta diversity in this subsample, potentially due to insufficient statistical power. Length of time that samples were stored prior to sequencing was associated with beta diversity (Q = 0.002, Bray Curtis dissimilarity). Six bacterial taxa were associated with age after adjustment for frailty and diet. Of the factors studied, frailty and age emerged as the most influential with regards to saliva microbiota composition. Whilst age and frailty are correlates, the associations were independent of each other, giving precedence to both biological and chronological ageing as processes of potential importance when considering saliva microbiota composition.

Indexed as

FrailtyMicrobiotaPeriodontal DiseasesAdultBacteriaHumansRNA, Ribosomal, 16SSalivaRNA, Ribosomal, 16S

Identifiers

PMID36344584
PMCPMC9640688

What Socratic holds

Textmetadata
LicenceCC BY
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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 Socratic graph.