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BackgroundWestern lifestyle is associated with high prevalence of allergy, asthma and other chronic inflammatory disorders. To explain this association, we tested the ‘biodiversity hypothesis’, which posits that reduced contact of children with environmental biodiversity, including environmental microbiota in natural habitats, has adverse consequences on the assembly of human commensal microbiota and its contribution to immune tolerance.MethodsWe analysed four study cohorts from Finland and Estonia (n = 1044) comprising children and adolescents aged 0.5–20 years. The prevalence of atopic sensitization was assessed by measuring serum IgE specific to inhalant allergens. We calculated the proportion of five land-use types – forest, agricultural land, built areas, wetlands and water bodies – in the landscape around the homes using the CORINE2006 classification.ResultsThe cover of forest and agricultural land within 2–5 km from the home was inversely and significantly associated with atopic sensitization. This relationship was observed for children 6 years of age and older. Land-use pattern explained 20% of the variation in the relative abundance of Proteobacteria on the skin of healthy individuals, supporting the hypothesis of a strong environmental effect on the commensal microbiota.ConclusionsThe amount of green environment (forest and agricultural land) around homes was inversely associated with the risk of atopic sensitization in children. The results indicate that early-life exposure to green environments is especially important. The environmental effect may be mediated via the effect of environmental microbiota on the commensal microbiota influencing immunotolerance.

Asthma prevalence has increased in epidemic proportions with urbanization, but growing up on traditional farms offers protection even today. 1 The asthma-protective effect in farms appears to be associated with rich home dust microbiota, 2,3 which could be used to model a health-promoting indoor microbiome. Here we show by modelling differences in house dust microbiota composition between farm and non-farm homes of Finnish birth cohorts 4 that in children who grow up in non-farm homes asthma risk decreases as the similarity of their home bacterial microbiota composition to that of farm homes increases. The protective microbiota had a low abundance of Streptococcaceae relative to outdoor-associated bacterial taxa. The protective effect was independent of richness and total bacterial load and was associated with reduced proinflammatory cytokine responses against bacterial cell wall components ex vivo. We were able to reproduce these findings in a study among rural German children 2 and showed that children living in German non-farm homes with an indoor microbiota more similar to Finnish farm homes have decreased asthma risk. The indoor dust microbiota composition appears as a definable, reproducible predictor of asthma risk and a potential modifiable target for asthma prevention. MAIN TEXTFrom ancient times, humans have adapted to rich microbial exposures in early life. Changes in these exposures in modern urbanized environments may drive the epidemic increases in asthma and allergies. 5,6 Many studies describe and identify protective microbial exposures but with heterogeneity in the specific microbial signals. Thus microbial exposures that could be exploited for preventive interventions remain unidentified. Here, we tested whether it is possible to circumvent this issue with an anchor-based method, drawing on the well-characterized asthma-protective effect of growing up on animal farms that appears associated with their particular indoor dust microbiota composition. 2,3 If the indoor microbiota in farm homes causally protects from asthma, as suggested by experimental data, 3,7,8 similar microbiota in non-farm homes should also have a protective effect despite the different surrounding environment and life-style.We characterized the indoor microbiota from living-room floor dust collected from the homes of Finnish birth cohorts, LUKAS1 and LUKAS2, 4,9 at the index child age of 2 months. At this age infants who crawl are constantly exposed to floor dust via the respiratory tract, skin and mouth. 10,11 The characteristics of the farm home microbiota were defined within LUKAS1, which includes only

Clinical phenotypes were well supported by LCA analysis. The hypothesis-free LCA phenotypes were a useful reference for comparing clinical phenotypes. Thereby, we identified children with clinically conspicuous but undiagnosed disease. Because of their high area under the curve values, clinical phenotypes such as (recurrent) unremitting wheeze emerged as promising alternative asthma definitions for epidemiologic studies.

and the PASTURE study group IMPORTANCE Atopic dermatitis is an inflammatory, pruritic skin disease that often occurs in early infancy with a chronic course. However, a specific description of subtypes of atopic dermatitis depending on the timing of onset and progression of the disease in childhood is lacking.OBJECTIVE To identify different phenotypes of atopic dermatitis using a definition based on symptoms before age 6 years and to determine whether some subtypes are more at risk for developing other allergic diseases. DESIGN, SETTING, AND PARTICIPANTSThe Protection Against Allergy Study in Rural Environments (PASTURE) is a European birth cohort where pregnant women were recruited between August 2002 and March 2005 and divided in 2 groups dependent on whether they lived on a farm. Children from this cohort with data on atopic dermatitis from birth to 6 years of age were included.EXPOSURES Atopic dermatitis, defined as an itchy rash on typical locations from birth to 6 years. MAIN OUTCOMES AND MEASURESThe latent class analysis was used to identify subtypes of atopic dermatitis in childhood based on the course of symptoms. Multivariable logistic regressions were used to analyze the association between atopic dermatitis phenotypes and other allergic diseases. RESULTSWe included 1038 children; of these, 506 were girls. The latent class analysis model with the best fit to PASTURE data separated 4 phenotypes of atopic dermatitis in childhood: 2 early phenotypes with onset before age 2 years (early transient [n = 96; 9.2%] and early persistent [n = 67; 6.5%]), the late phenotype with onset at age 2 years or older (n = 50; 4.8%), and the never/infrequent phenotype (n = 825; 79.5%), defined as children with no atopic dermatitis. Children with both parents with history of allergies were 5 times more at risk to develop atopic dermatitis with an early-persistent phenotype compared with children with parents with no history of allergies. Both early phenotypes were strongly associated with food allergy. The risk of developing asthma was significantly increased among the early-persistent phenotype (adjusted odds ratio, 2.87; 95% CI, 1.31-6.31). The late phenotype was only positively associated with allergic rhinitis. CONCLUSIONS AND RELEVANCEUsing latent class analysis, 4 phenotypes of atopic dermatitis were identified depending on the onset and course of the disease. The prevalence of asthma and food allergy by 6 years of age was strongly increased among children with early phenotypes (within age 2 years), especially with persistent symptoms. These findings are important for the development of strategies in allergy prevention.

In recent years increasing attention has been given to the potential health effects of fungal exposure in indoor environments. We used large-scale sequencing of the fungal internal transcribed spacer region (ITS) of nuclear ribosomal DNA to describe the mycoflora of two office buildings over the four seasons. DNA sequencing was complemented by cultivation, ergosterol determination, and quantitative PCR analyses. Sequences of 1,339 clones were clustered into 394 nonredundant fungal operational taxonomical units containing sequences from 18 fungal subclasses. The observed flora differed markedly from that recovered by cultivation, the major differences being the near absence of several typical indoor mold genera such as Penicillium and Aspergillus spp. and a high prevalence of basidiomycetes in clone libraries. A total of 55% of the total diversity constituted of unidentifiable ITS sequences, some of which may represent novel fungal species. Dominant species were Cladosporium cladosporioides and C. herbarum, Cryptococcus victoriae, Leptosphaerulina americana and L. chartarum, Aureobasidium pullulans, Thekopsora areolata, Phaeococcomyces nigricans, Macrophoma sp., and several Malassezia species. Seasonal differences were observed for community composition, with ascomycetous molds and basidiomycetous yeasts predominating in the winter and spring and Agaricomycetidae basidiomycetes predominating in the fall. The comparison of methods suggested that the cloning, cultivation, and quantitative PCR methods complemented each other, generating a more comprehensive picture of fungal flora than any of the methods would give alone. The current restrictions of the methods are discussed.

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This review discusses the role of fungi and fungal products in indoor environments, especially as agents of human exposure. Fungi are present everywhere, and knowledge for indoor environments is extensive on their occurrence and ecology, concentrations, and determinants. Problems of dampness and mold have dominated the discussion on indoor fungi. However, the role of fungi in human health is still not well understood. In this review, we take a look back to integrate what cultivation-based research has taught us alongside more recent work with cultivation-independent techniques. We attempt to summarize what is known today and to point out where more data is needed for risk assessment associated with indoor fungal exposures. New data have demonstrated qualitative and quantitative richness of fungal material inside and outside buildings. Research on mycotoxins shows that just as microbes are everywhere in our indoor environments, so too are their metabolic products. Assessment of fungal exposures is notoriously challenging due to the numerous factors that contribute to the variation of fungal concentrations in indoor environments. We also may have to acknowledge and incorporate into our understanding the complexity of interactions between multiple biological agents in assessing their effects on human health and well-being.