The DOI matches its Crossref record; 54 of the 54 references it cites were found in a registry or an index.
Farm-like indoor microbiota in non-farm homes protects children from asthma development
Open accessAbstract
Asthma prevalence has increased in epidemic proportions with urbanization, but growing up on traditional farms offers protection even today1. The asthma-protective effect of farms appears to be associated with rich home dust microbiota2,3, which could be used to model a health-promoting indoor microbiome. Here we show by modeling differences in house dust microbiota composition between farm and non-farm homes of Finnish birth cohorts4 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 children2 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 to be a definable, reproducible predictor of asthma risk and a potential modifiable target for asthma prevention. Exposure to a farm-like house dust microbiome is associated with protection against asthma development in children living in urban environments.
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Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., Blondel, M., Müller, A., Nothman, J., Louppe, G., et al. (2012) · arXiv · doi:10.48550/arxiv.1201.0490 · Cited by 71,016
QIIME allows analysis of high-throughput community sequencing data
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Self-citationSchloss, P. D., Westcott, S. L., Ryabin, T., Hall, J. R., Hartmann, M., Hollister, E. B., Lesniewski, R. A., Oakley, B. B., Parks, D. H., Robinson, C. J., et al. (2009) · Applied and Environmental Microbiology · doi:10.1128/aem.01541-09 · Cited by 19,549
FLASH: fast length adjustment of short reads to improve genome assemblies
Magoč, T., & Salzberg, S. L. (2011) · Bioinformatics · doi:10.1093/bioinformatics/btr507 · Cited by 15,366
APE: analyses of phylogenetics and evolution in R language
Paradis, E., Claude, J., & Strimmer, K. (2004) · Bioinformatics · doi:10.1093/bioinformatics/btg412 · Cited by 11,335
Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample
Caporaso, J. G., Lauber, C. L., Walters, W. A., Berg-Lyons, D., Lozupone, C. A., Turnbaugh, P. J., Fierer, N., & Knight, R. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1000080107 · Cited by 9,711
Self-citationPredictive functional profiling of microbial communities using 16S rRNA marker gene sequences
Langille, M. G. I., Zaneveld, J., Caporaso, J. G., McDonald, D., Knights, D., Reyes, J. A., Clemente, J. C., Burkepile, D. E., Vega Thurber, R. L., Knight, R., et al. (2013) · Nature Biotechnology · doi:10.1038/nbt.2676 · Cited by 9,116
Self-citationBias reduction of maximum likelihood estimates
FIRTH, D. (1993) · Biometrika · doi:10.1093/biomet/80.1.27 · Cited by 5,035
STAMP: statistical analysis of taxonomic and functional profiles
Parks, D. H., Tyson, G. W., Hugenholtz, P., & Beiko, R. G. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btu494 · Cited by 4,191
Analysis of composition of microbiomes: a novel method for studying microbial composition
Mandal, S., Van Treuren, W., White, R. A., Eggesbø, M., Knight, R., & Peddada, S. D. (2015) · Microbial Ecology in Health & Disease · doi:10.3402/mehd.v26.27663 · Cited by 1,942
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Enabling sustainable agriculture through understanding and enhancement of microbiomes
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Boxberger, M., Cenizo, V., Cassir, N., & La Scola, B. (2021) · Microbiome · doi:10.1186/s40168-021-01062-5 · Cited by 247
Urbanized microbiota in infants, immune constitution, and later risk of atopic diseases
Lehtimäki, J., Thorsen, J., Rasmussen, M. A., Hjelmsø, M., Shah, S., Mortensen, M. S., Trivedi, U., Vestergaard, G., Bønnelykke, K., Chawes, B. L., et al. (2021) · Journal of Allergy and Clinical Immunology · doi:10.1016/j.jaci.2020.12.621 · Cited by 116
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Metadata
- Authors
- Kirjavainen, P. V., Karvonen, A. M., Adams, R. I., Täubel, M., Roponen, M., Tuoresmäki, P., Loss, G., Jayaprakash, B., Depner, M., Ege, M. J., Renz, H., Pfefferle, P. I., Schaub, B., Lauener, R., Hyvärinen, A., Knight, R., Heederik, D. J. J., von Mutius, E., & Pekkanen, J.
- Venue
- Nature Medicine
- Published
- 2019-06-17
- Volume
- 25
- Issue
- 7
- Pages
- 1089-1095
- ISSN
- 1078-8956 (ISSN-L)
- 1546-170X
- OpenAlex
- W2949675525
- Cited by
- 323
- References
- 54
- FWCI
- 25.57
- Type
- journal article
- Language
- en
- Open access
- green
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- Kirjavainen, P. V., Karvonen, A. M., Adams, R. I., Täubel, M., Roponen, M., Tuoresmäki, P., Loss, G., Jayaprakash, B., Depner, M., Ege, M. J., Renz, H., Pfefferle, P. I., Schaub, B., Lauener, R., Hyvärinen, A., Knight, R., Heederik, D. J. J., von Mutius, E., & Pekkanen, J. (2019). Farm-like indoor microbiota in non-farm homes protects children from asthma development. Nature Medicine. https://doi.org/10.1038/s41591-019-0469-4
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
