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The infant gut virome is associated with preschool asthma risk independently of bacteria

Nature Medicine volume 30, pages 138–148 (2024)Cite this article

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Abstract

Bacteriophage (also known as phage) communities that inhabit the gut have a major effect on the structure and functioning of bacterial populations, but their roles and association with health and disease in early life remain unknown. Here, we analyze the gut virome of 647 children aged 1 year from the Copenhagen Prospective Studies on Asthma in Childhood2010 (COPSAC2010) mother–child cohort, all deeply phenotyped from birth and with longitudinally assessed asthma diagnoses. Specific temperate gut phage taxa were found to be associated with later development of asthma. In particular, the joint abundances of 19 caudoviral families were found to significantly contribute to this association. Combining the asthma-associated virome and bacteriome signatures had additive effects on asthma risk, implying an independent virome–asthma association. Moreover, the virome-associated asthma risk was modulated by the host TLR9 rs187084 gene variant, suggesting a direct interaction between phages and the host immune system. Further studies will elucidate whether phages, alongside bacteria and host genetics, can be used as preclinical biomarkers for asthma.

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Fig. 1: Infant gut virome classes, lifestyle versus preschool asthma.
Fig. 2: Comparison of 1-year-old infant virome compositions at the virus family-level, between infants with and without preschool asthma.
Fig. 3: Signature viral families within the infant temperate virome versus preschool asthma and associations with host bacteria.
Fig. 4: Congruence between temperate virome and bacterial compositions.
Fig. 5: Virome signature scores in relation to bacteriome signature scores in the associations with preschool asthma.
Fig. 6: Virome asthma signature score associations with early life exposures.

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Data availability

Viral sequence files can be accessed through the European Nucleotide Archive (https://ebi.ac.uk) under project number PRJEB46943. The 16 S rRNA sequences are deposited at the Sequence Read Archive (SRA) repository under accession number PRJNA417357.

Participant-level personally identifiable data are protected under the Danish Data Protection Act and European Regulation 2016/679 of the European Parliament and of the Council (GDPR) that prohibit distribution even in pseudo-anonymized form. However, participant-level data can be made available under a data transfer agreement as part of a collaboration effort.

Code availability

Data analyses were carried out using R (v.4.2.1) as specified in the Methods. Code is available on GitHub (https://github.com/crlero/vir2asth).

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Acknowledgements

We thank the children and families of the COPSAC2010 cohort study for their support and commitment. We acknowledge and appreciate the unique efforts of the clinicians involved in the COPSAC2010 study who followed up on the children, collecting samples and establishing diagnoses. Finally, we acknowledge the work of the late Professor Hans Bisgaard, founder of COPSAC and head of the clinical research center for more than 25 years. He was a dedicated, innovative physician–scientist who pushed the asthma research field forward and contributed immensely to pediatric research. His work and ideas live on in the studies conducted in the birth cohort, and we thank him for being an inspiration to us all.

All funding received by COPSAC is listed at https://copsac.com. The Lundbeck Foundation (R16-A1694), the Ministry of Health (903516), the Danish Council for Strategic Research (0603-00280B) and the Capital Region Research Foundation have provided core support to the COPSAC research center. This work is supported by the Joint Programming Initiative ‘Healthy Diet for a Healthy Life’, specifically here, the Danish Agency for Science and Higher Education, Institut National de la Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE) and the Canadian Institutes of Health Research (Team Grant in Intestinal Microbiomics, Institute of Nutrition, Metabolism, and Diabetes, 143924). S.A.S. and M.A.R. are recipients of a Novo Nordisk Foundation project grant in basic bioscience (grant NNF18OC0052965). J.S. and D.S.N. are recipients of Novo Nordisk Foundation grant NNF20OC0061029. J.S. received funding from the Danish Council for Independent Research (8045-00081B). J.T. is supported by the BRIDGE Translational Excellence Program at the Faculty of Health and Medical Sciences, University of Copenhagen, funded by the Novo Nordisk Foundation (grant NNF18SA0034956). C.-E.T.P. is funded by the Lundbeck Foundation (grant R322-2019-2735). S.M. holds the Canada Research Chair in Bacteriophages. Y.Z. is recipient of a PhD scholarship from the Chinese Scholarship Council (CSC). B.C. is funded by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (grant agreement no. 946228).

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Authors and Affiliations

  1. Copenhagen Prospective Studies on Asthma in Childhood, Copenhagen University Hospital, Gentofte, Denmark

    Cristina Leal Rodríguez, Shiraz A. Shah, Morten Arendt Rasmussen, Jonathan Thorsen, Ulrika Boulund, Casper-Emil Tingskov Pedersen, Christina Egeø Poulsen, Casper Sahl Poulsen, Michael Widdowson, Bo Chawes, Klaus Bønnelykke & Jakob Stokholm

  2. Department of Food Science, University of Copenhagen, Copenhagen, Denmark

    Morten Arendt Rasmussen, Josué L. Castro-Mejía, Ling Deng, Frej Andreas Nøhr Larsen, Yichang Zhang, Dennis S. Nielsen & Jakob Stokholm

  3. Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark

    Casper-Emil Tingskov Pedersen

  4. Section of Microbiology, Department of Biology, University of Copenhagen, Copenhagen, Denmark

    Søren J. Sørensen

  5. Département de Biochimie, de Microbiologie, et de Bio-Informatique, Faculté des Sciences et de Génie, Université Laval, Québec City, QC, Canada

    Sylvain Moineau

  6. Groupe de Recherche en Écologie Buccale, Faculté de Médecine Dentaire, Université Laval, Québec City, QC, Canada

    Sylvain Moineau

  7. Félix d’Hérelle Reference Center for Bacterial Viruses, Université Laval, Québec City, QC, Canada

    Sylvain Moineau

  8. Université Paris-Saclay, INRAE, Agroparistech, Micalis Institute, Jouy-en-Josas, France

    Marie-Agnès Petit

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  1. Cristina Leal Rodríguez
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  2. Shiraz A. Shah
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Contributions

J.S., S.M., M.A.P. and D.S.N. contributed to the conception of the study. J.S. and C.L.R. were responsible for acquisition of data. C.L.R. performed statistical analyses, and generated tables and figures. C.L.R. has written the first draft of the manuscript with contributions from J.S., S.A.S., J.T. and M.A.R. J.C.L., L.D., Y.Z. and D.S.N. generated data. All co-authors have provided important intellectual input and interpretation of the results. All authors guarantee that the accuracy and integrity of any part of the work have been appropriately investigated and resolved. All authors have approved the final version of the manuscript. The corresponding author had full access to the data and had final responsibility for the decision to submit for publication. No honorarium, grant or other form of payment was given to any of the authors to produce this manuscript.

Corresponding author

Correspondence to Jakob Stokholm.

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J.T. has received speaking fee from AstraZeneca. S.A.S. has been a consultant for Profluent. D.S.N. has been a consultant for Pfizer and Sniprbiome. All other authors have no competing interests. The funding agencies did not have any role in the design and conduct of the study; collection, management, and interpretation of the data; or preparation, review or approval of the manuscript. No pharmaceutical company was involved in the study.

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Extended data

Extended Data Fig. 1 Incidence of preschool asthma in COPSAC2010.

Distribution of age at first asthma diagnosis for 133 children with preschool asthma by five years of age at the COPSAC2010 cohort. Each colored background panel represents 1 year.

Extended Data Fig. 2 Individual virome profiles.

a Proportion of core, common, and rare bacteriophages among children across different taxonomic levels (top: species (that is vOTUs or viral contig representatives); bottom: families (that is viral family-level clades)) shared by >50% (core), 21-50% (common), 1-20% (rare) and <1% (very rare), respectively. Each bar in the x-axis represents one child. b Lifestyle differences (that is temperate and virulent) between the core, common, and rare virome components for all children (n = 631). P-values (P) were two-sided and correspond to the Wilcoxon rank-sum test. The center of the boxes represents the median, their bounds represent the 25th and 75th centile and the lower and upper ends of whiskers represent the smallest/largest value, no further than 1.5 × IQR from the box-plot respective end.

Extended Data Fig. 3 Phage classes abundance and prevalence.

Mean relative abundance (mra) and prevalence distributions for the three different classes of bacteriophages.

Extended Data Fig. 4 Taxonomy and lifestyle in asthma.

Stratified analysis comparing relative viral abundances between asthmatic and healthy children (n = 133/498) according to the viral classes and lifestyles. The center of the boxes represents the median, their bounds represent the 25th and 75th centile and the lower and upper ends of whiskers represent the smallest/largest value, no further than 1.5 × IQR from the box-plot respective end.

Extended Data Fig. 5 Alpha diversity analyses.

Alpha diversity analyses (observed richness and Shannon index) for overall virome and according to lifestyle (temperate, virulent or unknown) between asthmatic and healthy children (n = 133/498). Two-sided P-values (P) correspond to logistic regression. P* denotes FDR-adjusted P. The center of the boxes represents the median, their bounds represent the 25th and 75th centile and the lower and upper ends of whiskers represent the smallest/largest value, no further than 1.5 × IQR from the box-plot respective end.

Extended Data Fig. 6 Beta-diversity analyses.

Reproducibility of beta diversity analyses across presence-absence metrics (that is Jaccard and UniFrac), abundance metrics (that is Aitchison and Canberra), combined metrics (that is weighted UniFrac), and across high-low taxonomic resolutions (that is vOTUs and VFCs). VFC: viral family clades; vOTUs: viral contigs. P-values (P) were two-sided and derived from PERMANOVA tests.

Extended Data Fig. 7 Virome asthma signature scores and asthmatic episodes.

Associations between virome signature scores and number of asthmatic episodes in the first three years of life were investigated univariately by generalised linear regressions with a quasi-poisson distribution and P-values (P) were two-sided. Points indicate the point estimate for incidence risk ratios with horizontal lines indicating the 95% confidence intervals on the number of asthmatic episodes by virome signature scores. Incidence risk ratios (y-axis) are on logarithmic scale (base 10). The incidence risk rate of asthma troublesome symptoms can be interpreted as the risk for each standard deviation increases in the scores. Results are presented as Total (all episodes in the entire 3-year window) and stratified for each year separately for the entire cohort (n = 631).

Extended Data Fig. 8 Bacterial hosts of the virome asthma fingerprint.

Chord diagram showing the relationship between sequence-predicted bacterial hosts (genus) and the main 19 viral family-clades (VFCs) making up the virome signature scores for asthma. Only bacterial hosts present in more than one vOTU of the elected VFCs are shown. Ribbons width indicates the number of vOTUs and ribbons color specifies the bacterial genus. Colored outer bands of the VFCs indicate the viral order cluster (VOC). Bacterial hosts predicted by sequence similarity are sorted based on the number of phage vOTUs belonging to the asthma signature VFCs (highest-top to lowest-bottom) and tagged with a red asterisk (*) if the bacterial genus was predictive for asthma as reported by Stokholm et al.6. Asthma signature VFCs are sorted based on the loadings (strongest-top to weakest-bottom).

Extended Data Fig. 9 Virome scores sensitivity analysis.

Full replica of Fig. 5 using the virome scores derived from the sensitivity analysis performed in a nested cross-validation model. For the full caption refer to main Fig. 5.

Extended Data Fig. 10 Signature VFCs from the nested 5-fold cross-validation.

Comparison between the signature VFCs contributing to the optimal set of loadings for the 10-times repeated 10-fold CV SPLs model (nmodels=100) using the entire cohort (n = 631) and the corresponding 5 outer-folds (nmodel=1) from the nested cross-validation model derived from the five partitions of the entire cohort (n1 = 505, n2 = 504, n3 = 506, n4 = 505, n5 = 504). Bars depict the median ± SD. VFCs: viral-family clades.

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Leal Rodríguez, C., Shah, S.A., Rasmussen, M.A. et al. The infant gut virome is associated with preschool asthma risk independently of bacteria. Nat Med 30, 138–148 (2024). https://doi.org/10.1038/s41591-023-02685-x

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