Goh, Charlene E

ABSTRACT Aim To systematically review and meta‐analyze cohort studies evaluating associations of gingival inflammation, periodontitis, and tooth loss with cognitive decline and incident mild cognitive impairment or dementia. Methods PROSPERO‐registered searches of MEDLINE, Embase, Scopus, Web of Science, and the Cochrane Library identified cohort studies from inception through October 10, 2025, with a PubMed update on June 24, 2026. Random‐effects meta‐analyses pooled adjusted hazard ratios (HRs) for dementia/MCI; cognitive function outcomes were summarized qualitatively. Risk of bias (RoB) was assessed using the Newcastle–Ottawa Scale. Results Fifty‐nine studies met inclusion criteria; 28 contributed to dementia/MCI meta‐analyses. Severe periodontitis (HR: 1.16; 95% CI: 1.06–1.27; I 2 = 0%; Q ‐test p = 0.49), periodontitis of unspecified severity (HR: 1.45; 95% CI: 1.21–1.73; I 2 = 98%; Q ‐test p < 0.001), edentulism (HR: 1.26; 95% CI: 1.19–1.33), and low tooth count (HR: 1.27; 95% CI: 1.14–1.42; I 2 = 94%; Q ‐test p < 0.001) were associated with elevated dementia/MCI risk. RoB was low in 31 studies (53%), moderate in 25 (42%), and high in 3 (5%); inadequate confounder adjustment was common. Meta‐regression showed stronger estimates for ICD‐code periodontitis definitions (fold change (FC) = 1.44 95% CI: 1.04–2.01), older cohorts (FC per year = 1.02 95% CI: 1.00, 1.05), and weaker estimates with lower RoB (FC per NOS star = 0.81 95% CI: 0.73–0.92). Follow‐up duration, cohort age, and RoB were not associated with tooth‐count estimates. Conclusion Periodontitis and tooth loss are associated with modestly higher dementia/MCI risk and poorer cognitive function, but heterogeneity, residual confounding, and bias temper causal interpretation. Longitudinal studies with rigorous baseline cognition assessment and intervention studies are needed.

ABSTRACT Aims To investigate whether the association between the nitrite‐generating capacity of the subgingival microbiome and early cardiometabolic risk biomarkers varies by dietary nitrate intake. Materials and Methods Cross‐sectional data from 668 participants (mean age 31 ± 9 years, 73% women) were analysed. Dietary nitrate intake was calculated from food frequency questionnaires. Subgingival 16S rRNA sequencing (Illumina, MiSeq) and PICRUSt2 estimated microbial genes. The Microbiome‐Induced Nitric Oxide Enrichment Score (MINES) was calculated as a ratio of microbial gene abundances representing enhanced net capacity for NO generation. Adjusted multivariable linear models regressed cardiometabolic risk biomarkers (HbA1c, glucose, insulin, insulin resistance (HOMA‐IR), blood pressure) on nitrate intake and MINES together with a MINES × nitrate intake interaction term. Results Mean nitrate intake was 190 ± 171 mg/day. Significant interactions of MINES and nitrate intake were observed for insulin and HOMA‐IR ( p < 0.05). Among participants with a low MINES, higher nitrate intake was associated with lower HOMA‐IR (1.2 [1.1–1.4] vs. 1.5 [1.3–1.6]; p = 0.002), but levels were similar in those with high MINES ( p = 0.84). Conclusions A biomarker of higher microbial NO‐generating capacity in subgingival plaque is associated with lower insulin and insulin resistance among individuals with lower dietary nitrate intake. Future trials evaluating the cardiometabolic benefits of nitrate‐rich diets should incorporate measures of the entire oral microbiome.

Abstract Background Although periodontitis and oral microbiota are linked to cardiometabolic diseases (CMD), it is unclear if they similarly predict CMD mortality. We compared the predictive ability of salivary microbiota and periodontal disease measures for CMD mortality in the National Health and Nutrition Examination Survey (NHANES). Methods We included 5,037 adults aged ≥30 years (mean age [± standard deviation (SD)]: 48[± 14]; 50% male) from the 2009–2010 and 2011–2012 NHANES cycles. We used 16S rRNA sequencing data from saliva to operationalize microbial composition and diversity. We calculated the relative abundance log‐ratio of Treponema (linked with periodontal disease) to Corynebacterium (linked with periodontal health) to compute the Microbial Indicator of Periodontitis (MIP). Interproximal periodontal probing depth and clinical attachment loss were measured from periodontal examinations. Mortality was ascertained through 2019. Survey‐weighted Cox models regressed mortality rates on MIP, microbial diversity, and periodontal measures to estimate hazard ratios and 95% confidence intervals (HR [95% CI]). Results Over 8.8 median follow‐up years, there were 81 CMD and 267 all‐cause deaths. After multivariable adjustment, MIP was associated with increased CMD mortality risk (HR per 1‐SD: 2.10 [1.30–3.38]). Neither microbial diversity nor periodontitis measures were associated with CMD mortality. MIP was associated with periodontitis in multivariable modeling (risk ratio per 1‐SD: 1.29 [1.22–1.39]). Conclusions In a nationally representative cohort, greater baseline salivary Treponema to Corynebacterium ratio predicted increased CMD mortality risk, while microbial diversity metrics and periodontal parameters were not significantly associated with CMD mortality. Longitudinal studies that further contextualize the oral microbiota are warranted. Plain Language Summary Bacteria in the mouth that cause gum disease are linked to cardiometabolic diseases (e.g., diabetes, cardiovascular disease, kidney disease). However, it is not well understood if bacteria of the mouth can predict the risk of death due to cardiometabolic diseases. We used data from a nationwide survey of US adults to explore whether bacteria from saliva, collected from a single time point, are associated with the future risk of cardiometabolic disease death. We found that people with higher levels of gum disease bacteria were more likely to die from cardiometabolic diseases. Future studies are needed to better understand the role of gum disease bacteria in the development of cardiometabolic diseases and the risk of death.

ABSTRACTObjectiveTo study the association between dietary patterns and subgingival microbiota.MethodsParticipants (n = 651) who were enrolled in the Oral Infections, Glucose Intolerance, and Insulin Resistance Study (ORIGINS) with subgingival plaque sampling (n = 890 plaques) and a dietary assessment were included. 16S rRNA gene amplicon sequences of subgingival plaque from sites with either probing depth <4 or ≥4 mm were processed separately and used to obtain α‐diversity metrics (Faith, Shannon, Simpson, Observed) and taxa ratios (Red Complex to Corynebacterium [RCLR], Treponema to Corynebacterium [TCLR], and Treponema to Neisseria [TNLR]). Food frequency questionnaires (FFQs) were processed to calculate Alternate Healthy Eating Index (AHEI) and A Priori Diet Quality Score (APDQS) scores. Mixed regression models examined the mean levels of microbial metrics across quartiles of diet quality. Means ± standard errors are reported along with p‐values.ResultsIn multivariable models assessing the association between diet scores and α‐diversity metrics, higher AHEI values were significantly associated with lower Faith (p‐value = 0.01) and Observed (p‐value = 0.04) diversity values; similar findings were observed for APDQS (p‐value = 0.01, p‐value = 0.04). In multivariable models assessing the association between diet scores (AHEI and APDQS) and taxa ratios (RCLR, TCLR and TNLR), as the AHEI quartile increased, all taxa ratios decreased significantly as follows: −1.06 ± 0.093 in Q1 to −1.34 ± 0.099 in Q4 (RCLR), −0.43 ± 0.077 in Q1 to −0.64 ± 0.083 in Q4 (TCLR) and −0.09 ± 0.083 in Q1 to −0.38 ± 0.089 in Q4 (TNLR), respectively. In contrast, as the APDQS quartiles increased, only TNLR decreased significantly from −0.08 ± 0.085 in Q1 to −0.34 ± 0.091 in Q4.ConclusionDiets rich in fruits, vegetables, whole grains and other nutritionally rich plant foods are associated with lower oral microbial diversity and favourable ratios of pathogenic to commensal microbiota.