Periodic Reporting for period 4 - BRuSH (Oral bacteria as determinants for respiratory health)
Période du rapport: 2023-07-01 au 2025-02-28
The 2010 Global Burden of Disease has estimated that 3.9 billon people worldwide have poor dental health. According to the WHO, 300 million people have asthma. The prevalence of COPD and asthma is expected to increase because of increasing life expectancy and an aging population. Both periodontal diseases and chronic lung diseases will increase in the coming years due to increasing life expectancy and an aging population. Both disease conditions occur more often in groups with low socio-economic status, and lead to poorer quality of life for those affected. Periodontitis are the most common cause of lost teeth during the lifetime. Symptoms of periodontitis could be bleeding when brushing teeth and during dental flossing, redness, and edema of the gums. Periodontitis are heritable but are also affected by age and lifestyle. Early diagnostics and treatment are important to prevent the disease from developing into more severe forms. The decline in use of dental care is most pronounced among individuals of low social status, and social inequalities in dental health and use of dental care services are evident among elderly in Norway as well as in other European countries. The goal of BRuSH is to prove a causal relationship between oral microbiome and lung health, and gain knowledge that will enable us to make oral health a feasible target for intervention programs aimed at optimizing lung health and preventing respiratory disease.
The objective of BRuSH is first to explore whether the relative abundance of hexa-, penta-, and tetra-acylated LPS-producing bacteria in gingival and dust samples are associated with asthma severity, changes in lung function and respiratory diseases status over time. Secondly, to investigate whether the levels of LPS in oral and dust samples are associated with those outcomes; and whether the contribution of hexa-, penta-, and tetra-acylated LPS-producing bacteria influences these LPS levels. Third, to apply synthetized lipid As in mice models of experimental asthma and in vitro models of human bronchial epithelial cells. To reach these goals, BRuSH will use data and biobank material from two large population-based studies; the RHINESSA generation study (Respiratory Health In Northern Europe, Spain and Australia; www.RHINESSA.net) and the ECRHS study (European Community Respiratory Health Survey; www.ecrhs.org) and in addition in vitro and in vivo models to test how different lipid As influence lung health.
With longitudinal data and follow-up every 10th year, we can also establish that reporting often or always to bleed from the gums during toothbrushing are a strong predictor for reporting periodontitis 10 years later. With a multi-center design, we can also establish that there are differences between the Nordic countries and some of these difference are most likely due to cost and access of dental care.
Indoor air particle were sampled in homes of 1200 participants in the ECRHS study from five cites in Northern Europe. The samples were analyzed for bacteria and endotoxin. Proteobacteria were more abundant in Aarhus and Tartu, while Actinobacteria were more abundant in Bergen and Reykjavik than in other Nordic cities. Tartu showed the highest bacterial richness and Bergen the lowest. The same pattern was evident for endotoxin. We find that 54%of the bacteria were penta-acylated lipid A producing bacteria and only 3% were the potent hexa-acylated lipid A producing bacteria, and 30% gram-positive bacteria. The protocol for for the EDCs that were used to collect the airborne particles indoors were optimized to extract sufficient biomass to allow for both endotoxin and microbiome analyses. Climatic factors such as precipitation, wind and temperature were the most important determinants for explaining the differences in indoor bacterial composition between the five Nordic cities. Other factors that were important determinants were keeping a dog, sleeping with the window open, the age of the person living in the house and the number of persons in the homes, in addition to cleaning frequency.
 
           
        