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Published on: April 22, 2019
Oral microbiome and risk of incident head and neck cancer: A nested case-control study
Zeni Wu1, Yongli Han1, Yunhu Wan1
1Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA.
Objectives:
This nested case-control study in the NIH-AARP Diet and Health Study was carried out to prospectively investigate the relationship of oral microbiome with head and neck cancer (HNC).
Materials And Methods:
56 incident HNC cases were identified, and 112 controls were incidence-density matched to cases. DNA extracted from pre-diagnostic oral wash samples was whole-genome shotgun metagenomic sequenced to measure the overall oral microbiome. ITS2 gene qPCR was used to measure the presence of fungi. ITS2 gene sequencing was performed on ITS2 gene qPCR positive samples. We computed taxonomic and functional alpha-diversity and beta-diversity metrics. The presence and relative abundance of groups of red-complex (e.g., Porphyromonas gingivalis) and/or orange-complex (e.g., Fusobacterium nucleatum) periodontal pathogens were compared between cases and controls using conditional logistic regression models and MiRKAT.
Results:
Participants with higher taxonomic microbial alpha-diversity had a non-statistically significant decreased risk of HNC. No case-control differences were found for beta diversity by MiRKAT model (all p > 0.05). A greater relative abundance of red-complex periodontal pathogens (OR = 0.51, 95 % CI = 0.26-1.00), orange-complex (OR = 0.38, 95 % CI = 0.18-0.83), and both complexes' pathogens (OR = 0.32, 95 % CI = 0.14-0.75), were associated with reduced risk of HNC. The presence of oral fungi was also strongly associated with reduced risk of HNC compared with controls (OR = 0.39, 95 % CI = 0.17-0.92).
Conclusion:
Greater taxonomic alpha-diversity, the presence of oral fungi, and the presence or relative abundance of multiple microbial species, including the red- and orange-complex periodontal pathogens, were associated with reduced risk of HNC. Future studies with larger sample sizes are needed to evaluate these associations.
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