Oral microbiome signatures for gestational diabetes detection and prediction: a systematic review and evidence map
DOI:
https://doi.org/10.34310/jbsh.v3.i2.357Keywords:
oral microbiome, gestational diabetes mellitus, periodontal pathogens, systematic review, risk of biasAbstract
Background: Gestational diabetes mellitus (GDM) shares inflammatory and microbial pathways with periodontal disease. Whether the maternal oral microbiome could support GDM detection or prediction has not been comprehensively mapped. Methods: A systematic review followed PRISMA 2020 guidance across web-based, PubMed/PMC-indexed, and publisher sources plus citation chasing and a free-database supplementary search (ten primary search iterations plus two database-equivalent saturation checks, last updated 30 June 2026). Eligible studies compared pregnant women with and without GDM using a direct oral microbial measurement. Risk of bias was assessed using QUADAS-2, PROBAST, or Newcastle-Ottawa Scale/JBI tools according to design. Results: Of 36 records identified, 14 studies (2008-2026, six countries) met the inclusion criteria. Six used community-level 16S rRNA sequencing, seven used targeted pathogen quantification, and one combined cohort profiling with mechanistic and interventional components. Only two studies reported a discrimination model (area under the curve up to 0.89), and only two sampled the oral cavity before diagnosis; the remaining twelve measured it at or after diagnosis or within indeterminate timing windows. Most studies carried unclear or high risk of bias, particularly because confounder adjustment (including pre-pregnancy body mass index, confirmed in one open-access cohort to abolish most raw associations) and temporality were inadequately reported or methodologically problematic. Conclusion: Maternal oral dysbiosis is repeatedly but heterogeneously associated with GDM, and the evidence for using it as a detection or prediction tool remains preliminary, heterogeneous, and dominated by cross-sectional, post-diagnosis designs. Prospective, confounder-adjusted studies with externally validated prediction models are needed before clinical translation.
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