Oral health & preventive dentistry · 2026
Multivariate Genome-Wide Analysis Delineates Shared Genetic Determinants Across Periodontal and Oral Microbial Phenotypes.
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Zhang Yamei, Chen Mengshan, Zhang Fang
Аннотация
BACKGROUND: Periodontitis affects approximately 10% of the global population, posing a serious threat to tooth retention and quality of life. The disease emerges from bidirectional host-microbiome interactions that can shift from homeostasis to dysbiosis and chronic inflammation, yet conventional single-phenotype analyses cannot resolve pleiotropic loci acting across interrelated periodontal and microbial traits. We aimed to jointly model the shared genetic structure of six periodontitis-related phenotypes and to prioritise pleiotropic loci with translational relevance.
METHODS AND MATERIALS: We harmonised European-ancestry genome-wide association studies (GWAS) summary statistics for six traits representing host periodontal phenotypes (gingivitis, chronic periodontitis, periapical abscess, dental calculus) and oral microbial composition (genus Porphyromonas, order Bacteroidales). A common genetic factor was estimated using genomic structural equation modelling (genomic SEM), and factor-level genome-wide association analysis was conducted on 4,899,781 SNPs. The resulting signals were annotated through locus discovery and novelty assessment (FUMA), fine-mapping (SuSiE and FINEMAP), gene-level testing (MAGMA), and transcriptome-wide association with Bayesian gene prioritisation (FUSION and FOCUS). Heritability was partitioned across functional annotations (stratified LD score regression), and cell types (CELLECT); spatial enrichment was assessed using gsMap, and a polygenic risk score was constructed with PRS-CS.
RESULTS: A single-factor model provided adequate fit (CFI = 1.0). Factor-level GWAS identified 127 genome-wide significant SNPs consolidating into 56 independent lead variants, all uniquely identified at the factor level. MAGMA prioritised RASAL2 and C5orf27. Fine-mapping yielded 56 variants with posterior inclusion probabilities exceeding 0.95. Transcriptome-wide association and FOCUS converged on the long non-coding RNA RP11-563N4.1 (PIP = 1). Cell-type enrichment highlighted a vascular-stromal axis led by hepatic sinusoidal endothelial cells, with additional signals in pericytes, cardiac and smooth muscle cells, endocardium, and lung stroma. Spatial mapping localised the strongest aggregate signal to lung tissue, consistent with an oral-lung mucosal axis. Polygenic risk was distributed unevenly across chromosomes.
CONCLUSIONS: These analyses delineate a vascular-matrix-centred genetic architecture shared across periodontal and oral microbial traits. The prioritised loci and effector genes provide genetically informed candidates for risk stratification and for targeted investigation of periodontal pathobiology. Clinically, these genetically informed candidates may aid in identifying individuals at elevated risk and in guiding mechanism-based preventive and therapeutic strategies for periodontitis.
METHODS AND MATERIALS: We harmonised European-ancestry genome-wide association studies (GWAS) summary statistics for six traits representing host periodontal phenotypes (gingivitis, chronic periodontitis, periapical abscess, dental calculus) and oral microbial composition (genus Porphyromonas, order Bacteroidales). A common genetic factor was estimated using genomic structural equation modelling (genomic SEM), and factor-level genome-wide association analysis was conducted on 4,899,781 SNPs. The resulting signals were annotated through locus discovery and novelty assessment (FUMA), fine-mapping (SuSiE and FINEMAP), gene-level testing (MAGMA), and transcriptome-wide association with Bayesian gene prioritisation (FUSION and FOCUS). Heritability was partitioned across functional annotations (stratified LD score regression), and cell types (CELLECT); spatial enrichment was assessed using gsMap, and a polygenic risk score was constructed with PRS-CS.
RESULTS: A single-factor model provided adequate fit (CFI = 1.0). Factor-level GWAS identified 127 genome-wide significant SNPs consolidating into 56 independent lead variants, all uniquely identified at the factor level. MAGMA prioritised RASAL2 and C5orf27. Fine-mapping yielded 56 variants with posterior inclusion probabilities exceeding 0.95. Transcriptome-wide association and FOCUS converged on the long non-coding RNA RP11-563N4.1 (PIP = 1). Cell-type enrichment highlighted a vascular-stromal axis led by hepatic sinusoidal endothelial cells, with additional signals in pericytes, cardiac and smooth muscle cells, endocardium, and lung stroma. Spatial mapping localised the strongest aggregate signal to lung tissue, consistent with an oral-lung mucosal axis. Polygenic risk was distributed unevenly across chromosomes.
CONCLUSIONS: These analyses delineate a vascular-matrix-centred genetic architecture shared across periodontal and oral microbial traits. The prioritised loci and effector genes provide genetically informed candidates for risk stratification and for targeted investigation of periodontal pathobiology. Clinically, these genetically informed candidates may aid in identifying individuals at elevated risk and in guiding mechanism-based preventive and therapeutic strategies for periodontitis.