Influential factors of saliva microbiota composition

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. Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Philippa M. Wells [verfasserIn] Daniel D. Sprockett [verfasserIn] Ruth C. E. Bowyer [verfasserIn] Yuko Kurushima [verfasserIn] David A. Relman [verfasserIn] Frances M. K. Williams [verfasserIn] Claire J. Steves [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2022

Übergeordnetes Werk:	In: Scientific Reports - Nature Portfolio, 2011, 12(2022), 1, Seite 11
Übergeordnetes Werk:	volume:12 ; year:2022 ; number:1 ; pages:11

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1038/s41598-022-23266-x

Katalog-ID:	DOAJ086169025

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allfields	10.1038/s41598-022-23266-x doi (DE-627)DOAJ086169025 (DE-599)DOAJ189247387ab94ca08f49bb85b9ed73be DE-627 ger DE-627 rakwb eng Philippa M. Wells verfasserin aut Influential factors of saliva microbiota composition 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. Medicine R Science Q Daniel D. Sprockett verfasserin aut Ruth C. E. Bowyer verfasserin aut Yuko Kurushima verfasserin aut David A. Relman verfasserin aut Frances M. K. Williams verfasserin aut Claire J. Steves verfasserin aut In Scientific Reports Nature Portfolio, 2011 12(2022), 1, Seite 11 (DE-627)663366712 (DE-600)2615211-3 20452322 nnns volume:12 year:2022 number:1 pages:11 https://doi.org/10.1038/s41598-022-23266-x kostenfrei https://doaj.org/article/189247387ab94ca08f49bb85b9ed73be kostenfrei https://doi.org/10.1038/s41598-022-23266-x kostenfrei https://doaj.org/toc/2045-2322 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 12 2022 1 11
spelling	10.1038/s41598-022-23266-x doi (DE-627)DOAJ086169025 (DE-599)DOAJ189247387ab94ca08f49bb85b9ed73be DE-627 ger DE-627 rakwb eng Philippa M. Wells verfasserin aut Influential factors of saliva microbiota composition 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. Medicine R Science Q Daniel D. Sprockett verfasserin aut Ruth C. E. Bowyer verfasserin aut Yuko Kurushima verfasserin aut David A. Relman verfasserin aut Frances M. K. Williams verfasserin aut Claire J. Steves verfasserin aut In Scientific Reports Nature Portfolio, 2011 12(2022), 1, Seite 11 (DE-627)663366712 (DE-600)2615211-3 20452322 nnns volume:12 year:2022 number:1 pages:11 https://doi.org/10.1038/s41598-022-23266-x kostenfrei https://doaj.org/article/189247387ab94ca08f49bb85b9ed73be kostenfrei https://doi.org/10.1038/s41598-022-23266-x kostenfrei https://doaj.org/toc/2045-2322 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 12 2022 1 11
allfields_unstemmed	10.1038/s41598-022-23266-x doi (DE-627)DOAJ086169025 (DE-599)DOAJ189247387ab94ca08f49bb85b9ed73be DE-627 ger DE-627 rakwb eng Philippa M. Wells verfasserin aut Influential factors of saliva microbiota composition 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. Medicine R Science Q Daniel D. Sprockett verfasserin aut Ruth C. E. Bowyer verfasserin aut Yuko Kurushima verfasserin aut David A. Relman verfasserin aut Frances M. K. Williams verfasserin aut Claire J. Steves verfasserin aut In Scientific Reports Nature Portfolio, 2011 12(2022), 1, Seite 11 (DE-627)663366712 (DE-600)2615211-3 20452322 nnns volume:12 year:2022 number:1 pages:11 https://doi.org/10.1038/s41598-022-23266-x kostenfrei https://doaj.org/article/189247387ab94ca08f49bb85b9ed73be kostenfrei https://doi.org/10.1038/s41598-022-23266-x kostenfrei https://doaj.org/toc/2045-2322 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 12 2022 1 11
allfieldsGer	10.1038/s41598-022-23266-x doi (DE-627)DOAJ086169025 (DE-599)DOAJ189247387ab94ca08f49bb85b9ed73be DE-627 ger DE-627 rakwb eng Philippa M. Wells verfasserin aut Influential factors of saliva microbiota composition 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. Medicine R Science Q Daniel D. Sprockett verfasserin aut Ruth C. E. Bowyer verfasserin aut Yuko Kurushima verfasserin aut David A. Relman verfasserin aut Frances M. K. Williams verfasserin aut Claire J. Steves verfasserin aut In Scientific Reports Nature Portfolio, 2011 12(2022), 1, Seite 11 (DE-627)663366712 (DE-600)2615211-3 20452322 nnns volume:12 year:2022 number:1 pages:11 https://doi.org/10.1038/s41598-022-23266-x kostenfrei https://doaj.org/article/189247387ab94ca08f49bb85b9ed73be kostenfrei https://doi.org/10.1038/s41598-022-23266-x kostenfrei https://doaj.org/toc/2045-2322 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 12 2022 1 11
allfieldsSound	10.1038/s41598-022-23266-x doi (DE-627)DOAJ086169025 (DE-599)DOAJ189247387ab94ca08f49bb85b9ed73be DE-627 ger DE-627 rakwb eng Philippa M. Wells verfasserin aut Influential factors of saliva microbiota composition 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. Medicine R Science Q Daniel D. Sprockett verfasserin aut Ruth C. E. Bowyer verfasserin aut Yuko Kurushima verfasserin aut David A. Relman verfasserin aut Frances M. K. Williams verfasserin aut Claire J. Steves verfasserin aut In Scientific Reports Nature Portfolio, 2011 12(2022), 1, Seite 11 (DE-627)663366712 (DE-600)2615211-3 20452322 nnns volume:12 year:2022 number:1 pages:11 https://doi.org/10.1038/s41598-022-23266-x kostenfrei https://doaj.org/article/189247387ab94ca08f49bb85b9ed73be kostenfrei https://doi.org/10.1038/s41598-022-23266-x kostenfrei https://doaj.org/toc/2045-2322 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 12 2022 1 11
language	English
source	In Scientific Reports 12(2022), 1, Seite 11 volume:12 year:2022 number:1 pages:11
sourceStr	In Scientific Reports 12(2022), 1, Seite 11 volume:12 year:2022 number:1 pages:11
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container_title	Scientific Reports
authorswithroles_txt_mv	Philippa M. Wells @@aut@@ Daniel D. Sprockett @@aut@@ Ruth C. E. Bowyer @@aut@@ Yuko Kurushima @@aut@@ David A. Relman @@aut@@ Frances M. K. Williams @@aut@@ Claire J. Steves @@aut@@
publishDateDaySort_date	2022-01-01T00:00:00Z
hierarchy_top_id	663366712
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author	Philippa M. Wells
spellingShingle	Philippa M. Wells misc Medicine misc R misc Science misc Q Influential factors of saliva microbiota composition
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topic_title	Influential factors of saliva microbiota composition
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title	Influential factors of saliva microbiota composition
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title_full	Influential factors of saliva microbiota composition
author_sort	Philippa M. Wells
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author_browse	Philippa M. Wells Daniel D. Sprockett Ruth C. E. Bowyer Yuko Kurushima David A. Relman Frances M. K. Williams Claire J. Steves
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title_sort	influential factors of saliva microbiota composition
title_auth	Influential factors of saliva microbiota composition
abstract	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.
abstractGer	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.
abstract_unstemmed	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.
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title_short	Influential factors of saliva microbiota composition
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Influential factors of saliva microbiota composition

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