affiliations:€¦ · web viewword count main text: 3,983 / 3,500. word count abstract: 375 /...

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Infant RSV prophylaxis and nasopharyngeal microbiota until six years of life: a sub-analysis of a randomized controlled trial

Wing Ho Mana,b,c, Nienke M. Scheltemaa, Melanie Clerc d, Marlies A. van Houtenb, Elisabeth E.

Nibbelkea, Niek B. Achtena, Kayleigh Arpa, Elisabeth A.M. Sandersa, Louis J. Bonta, Debby Bogaerta,d

Affiliations:a Department of Paediatric Immunology and Infectious Diseases, Wilhelmina Children’s

Hospital/University Medical Center Utrecht, Utrecht, The Netherlands;

b Spaarne Gasthuis Academy, Hoofddorp and Haarlem, The Netherlands;

c Department of Pediatrics, Leiden University Medical Center, Leiden, The Netherlands;

d Medical Research Council/University of Edinburgh Centre for Inflammation Research, Queen's

Medical Research Institute, University of Edinburgh, Edinburgh, United Kingdom.

Preferred degree (one only):

W H Man MD, N M Scheltema MD, M Clerc PhD, M A van Houten MD, E E Nibbelke MSc, N B

Achten MD, K Arp BASc, Prof E A M Sanders MD, Prof L J Bont MD, Prof D Bogaert MD

Correspondence to:

D. Bogaert, MD, PhD

Medical Research Council/University of Edinburgh Centre for Inflammation Research

Queen's Medical Research Institute, University of Edinburgh

47 Little France Crescent

EH16 4TJ, Edinburgh, United Kingdom

Email: [email protected]

Tel: +44 131 2426582

Author contributions

N.M.S, D.B. and L.J.B. designed the study. N.M.S., E.E.N. and N.B.A. collected data. K.A. was

responsible for the execution and quality control of the laboratory work. W.H.M., M.C., and D.B.

analyzed and interpreted data. W.H.M., M.A. van H., E.A.M.S, L.J.B. and D.B. wrote the paper. All

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mailto:[email protected]

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authors significantly contributed to interpreting the results, critically revised the manuscript for

important intellectual content, and approved the final manuscript.

Word count main text:

3,983 / 3,500.

Word count abstract:

375 / 250.

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Summary

Background Respiratory syncytial virus (RSV) infection during infancy is suggested to cause long-

term wheeze. In turn, wheeze has been associated with bacterial dysbiosis of the respiratory tract. We

investigated the effects of RSV prophylaxis by palivizumab during infancy in otherwise healthy

preterms on respiratory microbiota composition at one year and six years of age in participants of the

randomized, placebo-controlled MAKI trial.

Methods 429 infants born between 32-35 weeks of gestation randomly received palivizumab or

placebo during the RSV season of their first year of life. The trial is registered in the ISRCTN registry,

number ISRCTN73641710. In total, 395/429 (92%) children were followed for clinical symptoms

until six years of age. For this sub-analysis, the aim was to assess the impact of palivizumab during

infancy on the respiratory microbiota composition of the available samples at age one and six years.

We obtained nasopharyngeal swabs at age 12 months from 170/429 (40%) children and analyzed

145/170 of these by 16S-rRNA sequencing. At age six, 349 nasopharyngeal swabs were obtained of

which 349/395 (88%) were analyzed by 16S-rRNA sequencing. At age six, also lung function

(including reversible airway obstruction) was determined.

Findings The overall microbiota composition was significantly different (p=0·0185, R2 1.2%)

between the palivizumab and placebo group at 12 months of life, but not significant at 6 years of life

(p=0·0575, R2 0.7%). At 12 months of life, a significant lower abundance of the Staphylococcus-

dominated cluster, and increased abundance of biomarker species such as Klebsiella and a diverse set

of oral taxa including Streptococcus spp. was observed in children who had received palivizumab

early in life, whereas at age six years, a significant increased abundance of Haemophilus spp. and

lower abundance of Moraxella and Neisseriaceae spp. was observed in the prophylaxis group.

Absence of PCR-confirmed RSV infection in the first year of life was also significantly associated

with a higher abundance of Haemophilus spp. at age 6 years and a significantly lower abundance of

Moraxella and Neisseriaceae. Reversible airway obstruction (RAO) at age six was also positively

associated with Haemophilus abundance and negatively associated with the abundance of health-

associated taxa such as Moraxella, Corynebacterium, Dolosigranulum and Staphylococcus, even after

correction for RSV immunoprophylaxis (all: p < 0.05). Additionally, RAO was associated with a

significant increase in Streptococcus pneumoniae abundance.

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Interpretation Palivizumab in infancy in otherwise healthy preterm infants is associated with

persistent effects on the abundance of specific potentially pathogenic microbial taxa in the respiratory

tract. Several of the palivizumab-associated biomarker species were associated with reversible airway

obstruction at age six. Together, our results warrant further studies to shed light on the long-term

ecological effects and health consequences of palivizumab in infancy.

Funding This study was funded by MedImmune (grant ESR-14-10006)

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Research in context

Evidence before this study

Infant respiratory syncytial virus (RSV) infection has been associated with wheeze and asthma in later

childhood, but the pathophysiological mechanism is unclear. We hypothesized that the respiratory

microbiota plays an important role since wheeze has been associated with dysbiosis in the respiratory

tract. We searched PubMed for clinical trials published up to April 8 th, 2018, using the search terms

‘(Child[mh] OR Infant[mh]) AND ("Respiratory Syncytial Viruses"[mh] OR "Respiratory Syncytial

Virus Infections"[mh] OR "Respiratory Syncytial Virus"[tiab] OR palivizumab[mh]) AND

(microbiota[tiab] OR microbiome[tiab] OR “RNA, Ribosomal, 16S”[mh]) NOT Review[pt]’. Of the

eight records retrieved, three observational studies showed that the respiratory microbiota composition

of children during RSV infection is distinct from that of healthy children with especially an

overrepresentation of Haemophilus and Streptococcus spp. in RSV infected children. None of the

studies, however, investigated the impact of early life RSV prophylaxis on the respiratory microbiota

later in life.

Added value of this study

In this single-blind, randomized, placebo-controlled trial, we demonstrate that early life RSV

prophylaxis (palivizumab) in otherwise healthy pre-term infants impacts the respiratory microbiota

composition at age one and six. At age one this was mainly associated with reduced abundance of

Staphylococcus spp., and an overrepresentation of bacteria routinely classified as ‘oral flora’, whereas

at age six this was mainly associated with increased abundance of Haemophilus spp. and reduced

abundance of Moraxella and Neisseriaceae spp. Alternative analysis comparing microbiota following

PCR-confirmed RSV versus no proven RSV showed corroborating results. Furthermore, reversible

airway obstruction at age six, as a marker for asthma, was, among others, positively associated with

Haemophilus and multiple Streptococcus spp. and negatively associated with Moraxella spp.,

Neisseria spp. and the health-associated Corynebacterium and Dolosigranulum spp. independent of

intervention. Together, our findings suggest that palivizumab in early life in otherwise healthy

preterms has long-term ecology-mediated health consequences.

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Implications of all the available evidence

To date, no randomized clinical trial using palivizumab has been conducted to assess the direct link

between RSV infection during infancy in otherwise healthy pre-term infants and subsequent

respiratory microbiota alterations at school age. Our study findings substantially extend the current

knowledge on the relationship between early life RSV infection, and respiratory microbiota

development, with a potential link to asthma in later childhood. Our findings endorse studies to

unravel the mechanistical links between early life viral infections, and potential respiratory

microbiota-mediated effects on asthma. This will not only improve our understanding, but potentially

also inform on the potential benefits and ecological risks of future RSV preventive interventions.

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Introduction

Respiratory syncytial virus (RSV) is the most common cause of acute lower respiratory tract infection

(LRTI) worldwide in children younger than five years and remains a major cause of mortality in

developing countries.1 Severe RSV-related LRTI during infancy has been strongly associated with

asthma inception.2

The pathophysiological mechanism underlying the association between RSV infection and asthma

inception remains to be elucidated, but cumulating evidence alludes to the importance of the

respiratory microbiota as a possible mediator. For example, early life microbial colonization with

Corynebacterium and Dolosigranulum spp. have been associated with lower susceptibility to upper

and lower respiratory infections, wheeze and asthma in infants, toddlers and young children, whereas

early life Haemophilus, Streptococcus, and Moraxella spp. colonization have been associated with the

reciprocal.3–5 We and others demonstrated that these latter bacterial species are also overrepresented

during symptomatic RSV in early life, and that Haemophilus and Streptococcus spp. are associated

with immunomodulation during RSV disease and severity of RSV symptoms.6–9 In addition, a higher

abundance of Haemophilus and Streptococcus spp. appear to be associated with wheezing illness,8,10,11

whereas Moraxella spp. colonization has shown ambiguous associations with health and disease.12,13 In

all, data suggest that susceptibility to and severity of RSV infection is related to the bacterial ecology

in the respiratory tract during the acute stage of disease. We here hypothesize that RSV infection may

also skew the composition of the respiratory tract microbiota in the long term towards profiles

associated with asthma.

We previously reported that RSV prophylaxis by the monoclonal antibody palivizumab (MedImmune,

Gaithersburg, USA) substantially reduced the incidence of RSV infection in the first year of life with

coinciding reduction in recurrent wheeze in otherwise healthy preterm infants (MAKI trial). 14

However, in a recent single, assessor-blind follow-up study of this randomized, placebo-controlled

trial, no major impact of palivizumab on asthma or lung function at six years of age was observed

although there was a decrease in parent-reported asthma symptoms.15

We here investigated nasopharyngeal microbiota at age one and six years of participant of the MAKI

follow-up study to explore the link between palivizumab during infancy and subsequent respiratory

microbiota alterations at school age. We additionally studied the association of respiratory microbiota

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with reversible airway obstruction at age six, to assess how the variations in respiratory microbiota

associated with palivizumab are associated with respiratory health.

Methods

Study design and participants

In the MAKI trial 429 otherwise healthy preterm infants, born between 32 weeks and 1 day, and 35

weeks and 6 days of gestation, were enrolled between 2008 and 2010.14 Infants were younger than six

months of age at the start of the RSV season and were randomly assigned in a 1:1 ratio to receive

either palivizumab or placebo. Randomization was stratified according to gestational age and masking

was secured by an independent pharmacist who had generated a permuted-block randomization list.

To investigate early life viral infections, parents were instructed to take a nasopharyngeal swab in all

instances of upper or lower respiratory tract symptoms lasting more than one day until the first

birthday of their infant.14 These samples were stored for further analyses of RSV and other viral

infections.

The study team had been re-blinded after the first-year analysis. Parents provided separate written

informed consent for their child to participate in the follow-up study. The randomization code was

kept by an independent physician until the six-year follow-up was completed. Parents who had been

unblinded were instructed not to reveal treatment allocation to the researchers at follow-up. Details

about the design, definitions and protocol of the primary study and the follow-up study have been

previously described (ISRCTN73641710).14,15

The protocol was approved by the institutional review board at the University Medical Center Utrecht.

Written informed parental consent was obtained from all participants.

Procedures

At age one year transnasal nasopharyngeal swabs were obtained according to WHO standard

procedures from the last 40% of enrolled participants (figure 1, see also appendix).16 At age 6 years,

transnasal nasopharyngeal swabs were obtained from all participating children and reversible airway

obstruction was assessed, expressed as change in percentage predicted FEV0·5 after administration of

salbutamol, was measured as previously described.15

Bacterial DNA was isolated and quantified from the 170 available samples at age 12 months and all

available samples at age six (figure 1).17 In addition, we included a random subset of (first) respiratory

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infection samples from 81 children obtained in the first year of life. Only samples that fulfilled our

quality control standards, having DNA levels of ≥0·3 pg/µl above negative controls, were included for

further analysis. Amplification of the V4 hypervariable region of the 16S rRNA gene was performed

using barcoded universal primer pair 533F/806R. Amplicons were quantified by PicoGreen

(Thermofisher) and pooled in equimolar amounts. Amplicon pools of samples and controls were

sequenced using the Illumina MiSeq platform (San Diego, CA, USA) and processed in our

bioinformatics pipeline as previously described.5 Analysis included binning of operational taxonomic

units (OTUs) at 97% sequence identity (VSEARCH). The appendix provides detailed information

about each step in our bioinformatic analysis, including the trimming (Sickle), error correction

(BayesHammer), merging (PANDAseq), demultiplexing (QIIME), chimera removal of sequences

(UCHIME), the subsequent picking, annotation, and filtering of OTUs (SILVA), and the identification

and removal of potential contaminants (Decontam). To avoid OTUs with identical annotations, we

refer to OTUs using their taxonomical annotations combined with a rank number based on the

abundance of each given OTU. Sequence reads were submitted to the National Center for

Biotechnology Information Sequence Read Archive (accession number SRP141698).

In addition, identification of Streptococcus pneumoniae was done by qPCR targeting the autolysin

(lytA) gene.18

Assessments

Our predefined primary aim was to assess the impact of palivizumab during infancy on the respiratory

microbiota composition at age one and six years. Predefined secondary aims were assessment of the

impact of proven RSV infection in the first year of life on the respiratory microbiota composition at

age one and six years. Proven RSV infection was defined as having a respiratory infection with a

PCR-detected RSV, regardless of viral codetection and regardless of palivizumab. Additionally, in a

posthoc analysis, we excluded the children in the palivizumabarm who developed an RSV infection in

the first year of life in the comparisons of microbiota across treatment groups, as microbiota profiles

identified in these children may be more related to RSV infection than the lack of effect of

palivizumab. We also cross-sectionally studied the relationship between the respiratory microbiota and

reversible airway obstruction at age six.

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Statistical analysis

Data analysis was performed in R v3·4 within Rstudio v1·0.19 For all assessments, we consecutively

analyzed the effects on overall microbial community structure (beta diversity) and the relationships on

cluster level and individual bacterial taxon level. A p-value of less than 0·05 or a Benjamini-Hochberg

adjusted q-value less than 0·10 was considered statistically significant.

Beta diversity analysis

Nonmetric multidimensional scaling (NMDS) plots were used to visualize differences of total

microbiota communities. Statistical significance between treatment groups was calculated by adonis

(vegan, 1,999 permutations).

Cluster analysis

Unsupervised average linkage hierarchical clustering was performed as described previously.9

Random forests (RF) classifier analyses using VSURF and normalized relative abundance analysis

were performed to determine biomarker species that most discriminate between clusters, as described

previously.20,21 A Chi-square test was used to test for the association between clusters and treatment

groups. A two-sided Wilcoxon rank-sum test was used to test for the association between clusters and

reversible airway obstruction.

Individual bacterial taxon analysis

To identify specific microbial taxa associated with variables of interest, we used either

metagenomeSeq for discrete variables (i.e. palivizumab group) or RF regression analysis for

continuous variables (i.e. reversible airway obstruction). For metagenomeSeq we filtered on the 100

most abundant taxa and used a maximum of 100 iterations.22 We performed sparse RF regression

analysis using a 10-fold cross-validated VSURF procedure. Taxa that were selected at least 20% of the

time during the interpretation step, were deemed important. Variable importance was assessed by 100

RF iterations generating 10,000 trees and the association of these variables with reversible airway

obstruction was crudely estimated post-hoc using Pearson’s correlation.

Role of the funding source

The funder of the study had no role in study design, data collection, data analysis, data interpretation,

or writing of the report. WHM and DB had full access to all data in the study and the corresponding

author had final responsibility for the decision to submit for publication.

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Results

Characterization of nasopharyngeal microbiota

429 otherwise healthy preterm infants were recruited to the original study between April and

December of each year between 2008 and 2010, and assigned to receive either palivizumab (n=214) or

placebo (n=215). Nasopharyngeal samples were obtained of 170/429 (the last 40%) of participants of

the original study at age one year, of which 145/170 (85%) generated sufficient and high-quality

material for further analyses (figure 1). From the 395 participants who had agreed with follow-up until

6 years of life, a nasopharyngeal sample was obtained from 349 children (88%); 342/349 (98%) of

these samples generated sufficient and high-quality material for further analyses (baseline

characteristics in table 1).

In addition, a random subset of first respiratory infection samples from 81 children obtained by the

parents during the first year of life (median [IQR] age 6·3 [4·1-8·3] months), i.e. during palivizumab

prophylaxis, were processed, from which 66/81 (81%) generated sufficient and high-quality material

for further analyses. Data regarding the nasopharyngeal microbiota composition of these samples,

including the viral detection in the first year of life, are detailed in the appendix.

Microbiota characterization across the three sample sets showed a strong age-related development of

respiratory microbiota over time, with initially a predominance of Enterococcus, Chryseobacterium,

Rothia, Brevundimonas, and oral Streptococci in the first months of life, via emerging abundance of

Staphylococcus, Moraxella, Klebsiella, Serratia and Enterococcus spp. at age 12 months, towards

predominance of Haemophilus, Moraxella, S. pyogenes, Corynebacterium and Dolosigranulum at 6

years (n=118 paired samples, see supplemental data in appendix).

Palivizumab treatment during infancy is associated with the microbiota composition at age one

At 12 months of life, the microbiota profile shows high interindividual variation, and is represented by

similar clusters such as Staphylococcus, Klebsiella, Moraxella, S. pneumoniae & Rothia, and

emergence of clusters dominated by Chryseobacterium, Brevundimonas and Enterococcus spp.

(supplementary figure 1b). Interestingly, we observed a significant difference in overall microbial

community structure between the palivizumab and the placebo group (R2=1·3%, p=0·0185; figure

2a). On cluster level, the Staphylococcus-dominated profile was positively associated with the placebo

group (chi-square, p=0·00394; OR 0·28, 95% CI 0·11-0·68), with a posteriori plotting of all

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biomarker species in the NMDS ordination further underlining the validity of this association (figure

2a). On individual taxon level, we confirmed that, although not statistically significant,

Staphylococcus was more abundant in the placebo group compared to palivizumab (metagenomeSeq,

log2 fold change 1·4, q=0·105, figure 3a). We further observed a significantly higher abundance of a

range of gram negative environmental and oral bacteria in the palivizumab group including

Chryseobacterium, Sphingobacterium, Ochrobacterium and Brevundimonas spp. ranging between 3

and 8 Log2 fold (8 to 256 fold) higher abundances compared to the control group, and some more

modest effects on several other gram-negative spp. including Klebsiella and gram positive bacteria

like Dolosigranulum pigrum, Lactobacillus spp., Streptococcus spp. whereas Leuconostoc, a gram

positive lactic acid producing bacterium, was overrepresented in the placebo group.

The effect of palivizumab on the microbiota composition persists up to age six years

When evaluated at six years of age, we still observed a small though non-significant difference in

overall microbial community structure between the otherwise healthy preterm infants who were

treated with palivizumab and those who received placebo (R2=0·6%, p=0·0575; figure 2b).

Especially, at age six years the Haemophilus-dominated profile was strongly associated with the

palivizumab group (chi-square, p=0·02960; OR 1·88, 95% CI 1·06-3·33). On individual bacterial

taxon level, again the abundance of Haemophilus spp. as well as S. pyogenes were positively

associated with the palivizumab group with effect sizes ranging from 0·4-1·7 log2 fold (=1·3-3·2 fold;

figure 3b), whereas Moraxella, Corynebacterium and Neisseriaceae spp. were negatively associated

with palivizumab in the first year of life. A posteriori plotting of all biomarker species in the NMDS

ordination further supports the validity of the above associations (figure 2b).

Since palivizumab is not 100% effective in protecting against RSV infections (relative risk reduction

67%)14, several samples in the analyses at age one and 6 years of life were from children with a proven

RSV infection despite having received palivizumab. To rule out a potential confounding effect of

these ‘therapy failures’, we repeated above analyses, excluding the samples from children with proven

RSV infections from the palivizumab arm. This posthoc analyses had no effect on the result at age one

(R2=1·3%, p=0·0285; appendix) but even slightly increased the effect size at age 6 years (R 2 0·7%),

making the difference between randomization groups significant (p=0·0425; appendix). These results

suggest a true effect of RSV infection (and the reversed, i.e. prevention thereof) on microbiota

development.

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Finally, we also tested the effect of palivizumab on stability of microbiota development over time, and

observed significantly less stable microbiota development (i.e. higher Bray-Curtis distance between

consecutive samples) in children who had received palivizumab compared to the placebo group (for

details: see supplemental information appendix).

Infant RSV infection has similar effects compared to placebo treatment

To further understand whether above findings could be directly attributed to (prevention of) RSV

infections themselves or by an indirect ecological effect of palivizumab, we compared the overall

microbiota composition between infants with RSV infection who received palivizumab versus infants

with RSV infection who received placebo: acknowledging the limited power of these analyses, we

found no difference at year one (adonis, n=14, 5/14 had received palivizumab and 9/14 had received

placebo, p=0·3615) nor at year 6 (adonis, n=34, 8/34 had received palivizumab and 26/34 placebo,

p=0·6615) between those children. We also performed a posthoc stratified analysis comparing the

microbiota of cases with PCR-confirmed versus cases with no proven RSV infections: At 12 months

of age, we had samples from 14 children with a history of a PCR-confirmed infection and 132 children

with no history of a proven RSV infection. Acknowledging the limited power of this analysis, we

found no significant difference in overall microbial community structure between children 12 months

of age with and without a history of RSV infection (R2=0·5%, p=0·732; supplementary figure 2a).

At six years of life, we had 34 samples of children with a history of a proven RSV infection, whereas

308 children had no history of a proven RSV infection in the first year of life. We did not find a

significant difference in overall microbial community structure between children at age six with or

without a history of proven RSV infection (R2=0·5%, p=0·082), though the trend in microbiota

deviation in the children without a proven RSV infection was oriented towards a more Haemophilus-

dominated community (supplementary figure 2b). On species level, absence of PCR-confirmed RSV

infection in the first year of life was significantly associated with a higher abundance of Haemophilus

spp. at age 6 years and a significantly lower abundance of Moraxella and Neisseriaceae spp.

(metagenomeSeq, q<0·10, supplementary figure 3), in line with the effect of palivizumab.

Microbiota variation in relation to reversible airway obstruction

Next, we tested the cross-sectional associations between microbiota composition at age six and

reversible airway obstruction at age six. Reversible airway obstruction was significantly associated

with overall respiratory microbial composition (adonis, R2=0·8%, p=0·0335). On individual taxon

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level, cross-validated random forests analysis confirmed the negative association between M.

catarrhalis/nonliquefaciens, Corynebacterium propinquum, Dolosigranulum pigrum, Kocuria,

Granulicatella, Pantoea agglomerans, and Roseomonas with reversible airway obstruction. In

contrast, several Haemophilus spp. were positively related with reversible airway obstruction, as well

as S. pneumoniae, Cupriavidus and a low-abundant Corynebacterium (figure 4). Correcting for the

use of palivizumab in the first year of life did not change the results.

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Discussion

In this single, assessor-blind, randomized, placebo-controlled trial, we demonstrate that palivizumab

during infancy in otherwise healthy preterms is linked with significant changes in respiratory

microbiota composition at one year and six years following the intervention.

Surprisingly, the nasopharyngeal microbial community at year one was still dominated by

Staphylococcus, a profile that has been associated extensively with a respiratory community of

younger infants.3,5,12,23 Only at 6 years of life we observed the ‘classical’ distribution of microbial

profiles as previously observed in younger children 1-2 years of life, including Moraxella,

Streptococcus, Haemophilus and Corynebacterium plus or minus Dolosigranulum-dominated profiles.

In contrast to the children in the previous studies however, we studied preterm born children. A recent

study also demonstrated that the maturation of the gut microbiota of preterm born infants lags behind

that of full term born infants and has not caught up yet at four years of age. 24 This might explain our

findings for the respiratory microbiota as well, and might also in part influence the observed

microbiota differences between the palivizumab and placebo arms of this study.

In children that had received palivizumab in their first year of life, Staphylococcus was less present

and abundant at age 12 months, and their microbial community was less stable over time, suggesting

that palivizumab might accelerate the maturation of the nasopharyngeal microbiota. Whether this is

caused by the prevention of RSV infection or may be related to infections by other viruses remains to

be elucidated. Also, it is unclear whether this faster maturation is beneficial to respiratory health or not

but a previous study suggested that an expedited maturation of the respiratory microbiota early in life

is related with increased susceptibility to respiratory disease later on.5

At six years, we find a higher abundance of Haemophilus spp. and a lower abundance of Moraxella

spp. in children who received palivizumab compared to those who received placebo. Similar effects

were found when comparing children without versus with PCR-confirmed RSV infection in the first

year of life, which is in line with the previous findings that accelerated microbiota maturation, and

consequently reduced stability is associated with increased abundance of non-typeable H.

influenzae.5,12

Although our study design does not allow us to fully unravel the underlying mechanisms, our data

suggest that RSV infection in otherwise healthy preterm infants may have long-term beneficial

ecological effects with reduction of Haemophilus spp. This effect could for example be mediated by

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the induction of local antiviral responses in the airway epithelium25 or by inducing an adaptive

immune response to the co-colonizing bacterial potential pathogens at time of RSV infection.

Reversible airway obstruction, a core measure for characterizing asthma,26 was positively associated

with microbiota community composition, with palivizumab-associated microbes like Haemophilus

spp. positively and Moraxella and Neisseria spp. and health-associated Corynebacterium and

Dolosigranulum spp. being negatively correlated with reversible airway obstruction. Additionally, we

demonstrated that reversible airway obstruction was positively associated with bacterial species that

were previously reported to be associated with asthma, i.e. Streptococcus spp., including S.

pneumoniae, and gram-negative oral bacteria,11,27 and negatively correlated with presumed

commensals of the nasopharyngeal niche, i.e. Corynebacterium, Dolosigranulum and

Staphylococcus.28,29 In all, we previously showed that palivizumab affects the spectrum of viral

infections in infancy, and prevents wheezing in early life. However, on the long term these effects

seem to diminish, which may in part be explained by long-term ecological effects, including

enrichment of more pro-inflammatory bacterial species like Haemophilus and a reduction in potential

beneficial species.

Several limitations of our study should be recognized. First, our cohort of children that were treated

with palivizumab still contained several children (n=8) that had a symptomatic RSV infection in the

first year of life.14 In addition, we probably underestimated the true incidence of RSV infections in our

analyses comparing children with and without PCR-confirmed RSV infections, because these were

based on voluntary parental swab collection.14 Both phenomena may likely have led to an

underestimation of the true impact of proven RSV infection in infancy on respiratory microbiota later

in life, especially with regard to mild RSV infections. The fact that we find very similar results when

comparing children with and without palivizumab, with children without and with PCR-confirmed

RSV infection, however, supports the validity of our results; i.e. at age one, Staphylococcus is

overrepresented in both the placebo group and the children with proven RSV infection, and at age six,

Haemophilus is overrepresented and Moraxella is underrepresented in both the palivizumab group and

the children without proven RSV infection. Second, our study was primarily designed to study the

effects of early life RSV infection, but not of other viral infections on respiratory microbiota

composition at age six, whereas our results now indicate it might be important to study the potential

impact of all viral infections early in life on the respiratory ecosystem. Our data suggests that the

impact of RSV immunoprophylaxis on long-term respiratory microbiota composition is at least in part

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due to prevention of RSV infection since absence of PCR-confirmed RSV infection in the first year of

life was associated with individual bacterial taxa in a similar way to having received palivizumab. It is,

however, possible that these associations are mediated by other non-RSV viral infections, which as

reported previously, are increased observed in children receiving RSV prophylxis.30,31 Third, we lacked

power to analyze the effect of age and timing of viral infections, which might be extremely important

for long-term ecological and health effects. Fourth, our study only included three sampling moments

of respiratory microbiota, whereas we and others have demonstrated the value of frequent sampling in

studying long-term respiratory health and disease.3,4,28 Even though potential differences in baseline

microbiota between randomization groups cannot be ruled out, the fact that microbiota composition

during the first infections in early life were highly similar between groups, baseline differences

become highly unlikely. Fifth, our study sample was drawn from preterm born children between 32

and 35 weeks’ gestational age and is therefore not representative of the general population. A

comparator with term born babies might therefore be warranted for future studies. Sixth, it is highly

likely that all children, including those who received palivizumab, were infected with RSV at some

point beyond the first year of life. Our study design cannot ascertain this effect on the microbiota

composition at age six. It is, however, presumed that changes in respiratory microbiota composition in

early life -during the so-called “window of opportunity”- have more impact on respiratory health later

in life than microbiota changes later in life.28 Finally, 16S-rRNA sequencing can only examine the

bacterial microbiota, but not the viral or fungal microbiota, while an increasing body of evidence

suggests the importance of the respiratory virome and mycobiome in respiratory health and disease.28

This should be taking into consideration with new studies.

Nevertheless, our results suggest that albeit generating a major direct health benefit by prevention of

RSV infections, in early life, in this cohort of otherwise healthy preterm infants palivizumab seems to

affect the respiratory microbiota composition at age one and age six. At age six, palivizumab is

accompanied by the potentially unfavorable overrepresentation of Haemophilus spp. that, in turn, are

independent from the intervention, associated with reversible airway obstruction in our cohort. At the

least, our study findings suggest that viral infections in early life have an important role in shaping the

respiratory ecosystem long-term, possibly as a result of immune modulation during the essential phase

of early life immune maturation.32 These data may nuance the discussion regarding the effects of

universal prevention of RSV infection33, and provide a premise for further studies on early life

interactions between respiratory viruses, microbiota, and the host immune system, and their potential

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long-term consequences on the human ecosystem as well as asthma development. This is of critical

importance, especially in our population of otherwise healthy preterm children, as asthma is still one

of the leading and increasing causes of substantial disability in this group of children.

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Acknowledgements

The authors are indebted to all the participating children and their families for their commitment and

participation. We thank all members of the MAKI research team, including the staff of the pediatric

lung function laboratory, and the laboratory staff. We are grateful to Hicham el Madkouri for his

primary exploration of the data. This work was supported in part by the Netherlands Organisation for

Scientific Research (NWO-VIDI; grant 91715359) and CSO/NRS Scottish Senior Clinical Fellowship

award (SCAF/16/03).

Declaration of interests

E.A.M.S. declares to have received unrestricted research support from Pfizer, grant support for

vaccine studies from Pfizer and GSK. L.J.B. reports grants from AbbVie during the conduct of the

study and grants from MedImmune, Janssen, MeMed, and the Bill & Melinda Gates Foundation. D.B.

declares to have received unrestricted fees paid to the institution for advisory work for Friesland

Campina and well as research support from Nutricia. No other authors reported financial disclosures.

None of the other authors report competing interests.

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Tables and figures

Table 1. Baseline characteristics

Demographic characteristics of the children analyzed on year 1 (A) and year 6 (B). Baseline characteristics at randomization have been published and are available at NEJM.org.14

A

Placebo Palivizumab

n 66 79

Male (%) 34 (51·5) 51 (64·6)

Height in cm (median [IQR]) 116 [111, 119] 116 [113, 120]

Weight in kg (median [IQR]) 20·1 [18·6, 21·7] 20·4 [18·8, 21·8]

Any wheezing year 1 (%) 30 (46·9) 25 (31·6)

Recurrent wheezing year 1(%) 11 (16·7) 9 (11·4)

Pets (%) 31 (49·2) 35 (44·3)

Breastfeeding (%) 45 (75·0) 48 (67·6)

Maternal smoking during pregnancy (%) 10 (16·1) 16 (20·8)

Parental atopy (%) 35 (54·7) 53 (69·7)

Atopy Mother (%) 24 (38·1) 34 (43·0)

Asthma Mother (%) 12 (18·8) 9 (11·4)

Hay fever Mother (%) 15 (23·8) 19 (24·4)

Eczema Mother (%) 12 (18·8) 18 (22·8)

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Atopy Father (%) 18 (29·0) 31 (41·3)

Asthma Father (%) 6 ( 9·7) 10 (13·0)

Hay fever Father (%) 9 (14·5) 20 (26·0)

Eczema Father (%) 6 ( 9·5) 11 (14·7)

Parental smoking (%) 26 (39·4) 31 (39·2)

Smoking Mother (%) 11 (18·0) 13 (16·5)

Smoking Father (%) 18 (28·6) 26 (34·7)

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B

Placebo Palivizumab

n 166 176

Male (%) 81 (48·8) 109 (61·9)

Height in cm (median [IQR]) 116 [113, 119] 116 [113, 120]

Weight in kg (median [IQR]) 20·4 [18·9, 22·3] 20·9 [19·1, 22·6]

Any wheezing year 1 (%) 85 (51·5) 61 (35·1)

Recurrent wheezing year 1(%) 40 (24·2) 23 (13·1)

Pets (%) 79 (48·8) 80 (45·5)

Breastfeeding (%) 121 (74·7) 117 (72·2)

Maternal smoking during pregnancy (%) 23 (14·6) 24 (14·0)

Parental atopy (%) 98 (60·5) 110 (63·6)

Atopy Mother (%) 55 (34·2) 73 (41·5)

Asthma Mother (%) 17 (10·4) 18 (10·2)

Hay fever Mother (%) 33 (20·5) 46 (26·1)

Eczema Mother (%) 25 (15·3) 40 (22·7)

Atopy Father (%) 62 (38·5) 65 (37·8)

Asthma Father (%) 17 (10·7) 25 (14·4)

Hay fever Father (%) 41 (25·3) 37 (21·3)

Eczema Father (%) 19 (11·7) 26 (15·1)

Parental smoking (%) 57 (34·3) 61 (34·7)

Smoking Mother (%) 23 (14·6) 24 (13·8)

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Smoking Father (%) 43 (26·9) 47 (27·8)

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542

12 months NP swab

Availablen = 170

Participantsprimary study

n = 429

Participantsfollow-up study

n = 395

6 yearsNP swab

Availablen = 349

High quality DNAn = 145

High quality DNAn = 342

Palivizumabn = 79

Placebon = 66

Palivizumabn = 176

Placebon = 166

Primary analysis

Secondary analysis

16S sequencingn = 170

16S sequencingn = 349

Palivizumabn = 74#

Placebon = 66

No RSVn = 132

Proven RSV

n = 14

Palivizumabn = 168#

Placebon = 166

No RSVn = 342

Proven RSV

n = 34

Combinedn = 274

6 yearsSpirometry

Availablen = 290

Palivizumabn = 137

Placebon = 137

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Figure 1. Flow diagram for samples analyzed.

NP = nasopharynx. # We excluded 5/79 and 8/176 children from the palivizumab group in our posthoc

analyses of the children at age 12 months and 6 years, respectively, as they developed an RSV

infection during their first year of life. Including these samples yielded similar results (appendix).

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Figure 2. Microbiota profiles at age 12 months and 6 years.

(A) Three-dimensional NMDS plots depicting the individual nasopharyngeal microbiota composition

at year one (data points, n=145) colored by treatment group: placebo (brown, n=66) and palivizumab

(dark green, n=79). The difference in total microbiota composition in both groups is significant

(adonis, R2=1·3%, p=0·0185).

(B) Three-dimensional NMDS plots depicting the individual nasopharyngeal microbiota composition

at year 6 (data points, n=342) colored by treatment group: placebo (brown, n=166) and palivizumab

(dark green, n=176). The difference in total microbiota composition in both groups is smaller

compared to 12 months (R2 0·6% versus 1·3%), though still not significant (adonis, R2=0·6%,

p=0·0575). Ellipses represent the standard deviation of all points within a cohort. The stress-value

using the first two dimensions was 0·25, whereas this dropped to 0·18 when using three dimensions.

Because a stress of <0·2 indicates a reasonable interpretability,34 we decided to depicts the samples

across these three dimensions (NMDS1-NMDS3). The figures also depict the biomarkers species

(determined by random forests analysis on hierarchical clustering results) colored by phylum (Green

diamonds = Proteobacteria, orange triangles = Firmicutes, purple squares = Actinobacteria, pink

circles = Bacteroides). To avoid OTUs with identical annotations, we refer to OTUs using their

taxonomical annotations combined with a rank number based on the abundance of each given OTU.

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Figure 3. Differential abundance of bacterial taxa between treatment groups.

Effect sizes are depicted for the 20 most differentially abundant taxa in either the palivizumab group (right) or placebo group (left). Log2 fold changes (including 95% confidence intervals) were obtained by metagenomeSeq analysis and corrected for multiple comparisons (Benjamini-Hochberg). (A) depicts the results for samples (n = 145) obtained at 12 months of life, whereas (B) depicts the results for samples obtained 6 years of life (n = 342). To avoid OTUs with identical annotations, we refer to OTUs using their taxonomical annotations combined with a rank number based on the abundance of each given OTU.

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Figure 4. Sparse random forests models associating microbial species with reversible airway obstruction.

Twelve taxa were associated with reversible airway obstruction as selected by a cross-validated

random forests analysis using all samples (n=274). Taxa are ranked in descending order based on their

importance to the accuracy of the model. Variable importance was estimated by calculating the mean

increase in node purity after randomly permuting the values of each given variable (mean ± standard

deviation, 100 replicates). A higher value increase in node purity represents a higher variable

importance. The direction of the associations was estimated post-hoc using Pearson’s correlation (red

= positive association reversibility; blue = negative association with reversibility). To avoid OTUs

with identical annotations, we refer to OTUs using their taxonomical annotations combined with a

rank number based on the abundance of each given OTU. Whether children had received RSV

prophylaxis versus placebo in the first year is not significantly contributing to the model (gray).

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Supplementary appendix

Sampling at 12 months

Only during the last year of recruitment, we sampled children at 12 months. We saw no differences in

baseline characteristics between these last 40% children and the first 60% children of which we did

not have a 12-month sample (p>0·20 for all characteristics).

Additional methods for bioinformatics analysis

Raw sequences were trimmed using an adaptive, window-based trimming algorithm (Sickle, Q>20,

length threshold of 150 nucleotides).35 We aimed to further reduce the number of sequence errors in

the reads by applying an error correction algorithm (BayesHammer, SPAdes genome assembler

toolkit).36 Forward and reverse reads were then assembled into contigs using PANDAseq.37 Merged

reads were demultiplexed using QIIME (v1·9).38 After removal of singleton sequences, we removed

chimeras using both de novo and reference (against Gold database) chimera identification (UCHIME

algorithm in VSEARCH).39,40 VSEARCH abundance-based greedy clustering was used to pick OTUs

at a 97% identity threshold.41 Taxonomic annotation was executed using the RDP-II naïve Bayesian

classifier on SILVA v119 training set.42 Taxonomic assignment was validated by blasting against the

NCBI database, using a 100% identity cut-off. We generated an abundance-filtered dataset by

including only those OTUs that were present at or above a confident level of detection (0·1% relative

abundance) in at least two samples.43 In addition, to ensure our data was of the highest quality, we

identified and removed 58 potential contaminants using the Decontam R-package, as previously

described (supplementary figure 4).21 Also, we only kept samples that contained at least 9,000 reads.

To avoid OTUs with identical annotations, we refer to OTUs using their taxonomical annotations

combined with a rank number based on the abundance of each given OTU. In case when an OTU

could not be confidently annotated as either of two species, both species are indicated and separated

by a solidus. The raw OTU-counts table was used for calculations of alpha-diversity (local diversity)

and analyses using the metagenomeSeq package.22 The OTU-proportions table was used for all other

downstream analyses, including hierarchical clustering and random forests modelling. Beta-diversity

was assessed using the Bray-Curtis dissimilarity metric.

Sequence reads were submitted to the National Center for Biotechnology Information Sequence Read

Archive (accession number SRP141698).

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Quality control of 16S-rRNA gene amplicon sequencing

In total, 24 DNA isolation and PCR blanks were sequenced along with the study samples. All blanks

yielded <4,500 reads and the number of reads was more than one order of magnitude lower compared

to that of the samples (median 551 vs 37,529 reads; supplementary figure 5a). Hierarchical

clustering also clearly separated the blanks from samples (supplementary figure 5b). These results

robustly indicate that our strict sequencing protocol resulted in no apparent contamination.

Characterization of nasopharyngeal microbiota

Across all analyzed samples, 19,516,175 reads in total (mean 36,412 ± 19,513 reads/sample) were

retained for downstream analyses and these were binned into 309 operational taxonomic units (OTUs),

further referred to as bacterial taxa. For all samples the Good’s estimator of coverage was above

99·9%. The taxon annotated as “Streptococcus (6)” had a strong correlation with lytA qPCR Ct-values,

confirming its origin Streptococcus pneumoniae (Spearman’s rho -0·81, p<0·001). The dominant

phyla were Proteobacteria (47·5%), Firmicutes (34·8%), and Actinobacteria (15·9%). Hierarchical

clustering showed the presence of 15 distinct microbiota profiles (supplementary figure 1b) driven

by Moraxella catarrhalis/nonliquefaciens (28·3%), Staphylococcus (16·2%), Corynebacterium

propinquum & Dolosigranulum pigrum (14·4%), Haemophilus (11·2% of samples), Streptococcus

pneumoniae & Rothia (5·2%), Streptococcus pneumoniae (3·1%), Moraxella lincolnii (2·2%),

Moraxella osloensis (2·0%), Streptococcus salivarius (1·8%), Klebsiella (1·6%), Streptococcus

pyogenes (1·6%), Enterococcus faecium (1·3%), Chryseobacterium (1·1%), Moraxella lacunata

(1·1%), and Brevundimonas (0·9%).

Viruses and microbiota composition in the first year of life

In the subset of RTI samples, we detected a virus in 58/66 (87·9%) samples. RSV was detected in 1/66

of the subset of children (1·5%). The most common other virus was HRV, detected in 48/66 (72·7%)

of the children, followed by adenovirus (11/66 [16·7%]), and coronavirus (9/66 [13·6%];

supplementary table 1). The nasopharyngeal microbiota composition during those respiratory

infections was typified by microbiota dominated of Staphylococcus, followed by a.o. Klebsiella, S.

pneumoniae, Rothia and Moraxella spp. (supplementary figure 1a): microbiota did not differ

between the RSV prophylaxis group and the placebo group (adonis, R2 0·6%, p=0·981).

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Viruses in the first year of life

From the analyzed samples at 12 months, a total of 80/145 (55·1%) otherwise healthy preterm born

children experienced a PCR-confirmed viral infection in the first year of life. RSV was detected in

14/145 children 9·6%). The most common other virus was HRV, detected in 66/145 (45·5%) of the

children, followed by adenovirus (22/145 [15·2%]), and bocavirus (18/145 [12·4%]; supplementary

table 2a). There was a similar distribution of early life viral infection within our subset of samples at

age 12 months.

From the analyzed samples at 6 years, a total of 182/342 (53·2%) otherwise healthy preterm born

children experienced a PCR-confirmed viral infection in the first year of life. RSV was detected in

34/342 children 9·9%) and was detected significantly more in the placebo group compared to the RSV

prophylaxis group (8/166 [4·5%] and 26/176 [15·7%], respectively, p=0·001; supplementary table

2b). The most common other virus was HRV, detected in 158/342 (46·2%) of the children. HRV was

detected significantly more in the RSV prophylaxis group compared to the placebo group (87/176

[49·4%] and 71/166 [42·8%], respectively, p=0·027). The other viruses were detected equally across

treatment groups in the first year of life in the subset of the samples analyzed at year six.

Relationship between microbiota composition at age one and six

We confirmed that microbiota maturation continues from age 12 months to age 6 years with

significant differences in microbiota community compositions between both age groups (R 2=9·5%,

p<0·0001). Especially the biomarker taxa E. faecium, M. osloensis, Chryseobacterium, Rothia,

Brevundimonas, and S. salivarius diminished over time, whereas Haemophilus spp., M.

catarrhalis/nonliquefaciens, C. propinquum, D. pigrum, S. pyogenes, and M. lacunata increased

significantly with age (supplementary figure 7). Interestingly, although most children had a different

microbiota profile at age 6 years compared to age 12 months (n=118 paired samples, supplementary

figure 8), we still saw that there was a higher but not significant correlation between paired microbiota

of the same child at 12 months and 6 year of life when compared to unpaired samples (median Bray-

Curtis similarity 0·101 and 0·044, respectively; p=0.056; supplementary figure 9a) suggesting the

existence of a modest intra-individual core microbiome. This was strengthened by the fact that more

stable microbiota development between year 1 and year 6 samples was associated with the presence of

Moraxella catarrhalis/nonliquefaciens and Corynebacterium propinquum & Dolosigranulum pigrum-

dominated clusters (median Bray-Curtis similarity 0·455 and 0·348, respectively, versus 0·001-0·191

for all other clusters; supplementary figure 9b), corroborating previous studies suggesting the

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presence of these microbiota profiles in early life are associated with stable and resilient microbiota

development over time.

Interestingly, when stratifying for treatment groups, the existence of a core microbiome was only

evident for the placebo group (median Bray-Curtis similarity 0·126 and 0·039, for intra-individual

versus inter-individual concordance, respectively; p=0·03583; supplementary figure 9a) but not for

the palivizumab group (median Bray-Curtis similarity 0·054 and 0·045, respectively; p=0·475;

supplementary figure 9a), suggesting that children receiving placebo had more stable microbiota

development compared to the palivizumab group.

Findings excluding children within the palivizumab group who developed an RSV infection during their first year of life

We excluded 5/79 and 8/176 children from the palivizumab group in a posthoc analyses of the

children at age 12 months and 6 years, respectively, as they developed an RSV infection during their

first year of life. At 12 months of life, we observed a significant difference in overall microbial

community structure between the palivizumab and the placebo group (R2=1·3%, p=0·0285). On

cluster level, the Staphylococcus-dominated profile was positively associated with the placebo group

(chi-square, p=0·00381; OR 0·27, 95% CI 0·10-0·67). On individual taxon level, Staphylococcus

abundance was not different in the placebo group compared to palivizumab (metagenomeSeq, log2 fold

change 1·4, q=0·122, figure 10a). We further observed a significantly higher abundance of

Helcococcus, Dolosigranulum pigrum, Lactobacillus spp., Streptococcus spp. and a range of gram-

negative spp. including Klebsiella and several oral bacteria in the palivizumab group.

When evaluated at six years of age, we still observed a small though not significant difference in

overall microbial community structure between the otherwise healthy preterm infants who were

treated with palivizumab and those who were treated with placebo (R2=0·7%, p=0·0425). On cluster

level, the Haemophilus-dominated profile at age six years was positively associated with the

palivizumab group (chi-square, p=0·02571; OR 1·91, 95% CI 1·08-3·41). On individual bacterial

taxon level, Haemophilus spp. as well as S. pyogenes were positively associated with the palivizumab

group (figure 10b), whereas Moraxella, Corynebacterium and Neisseriaceae spp. were negatively

associated with palivizumab in the first year of life.

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Supplementary table 1. Prevalence of respiratory virus detection in the 66 RTI samples analyzed in this study.

None of the differences between treatment groups were statistically significant (Chi-square all p>0·4).

All RTI samples(n=66)

Placebo(n=33)

Palivizumab(n=33)

Virus n % n % n %

Any virus 58 87·9 28 84·8 30 90·9

Multiple viruses 20 30·3 8 24·2 12 36·4

Respiratory syncytial virus (RSV) 1 1·5 1 3·0 0 0

RSV with any other virus 1 1·5 1 3·0 0 0

Human rhinovirus 48 72·7 23 69·7 25 75·8

Adenovirus 11 16·7 4 12·1 7 21·2

Bocavirus 7 10·6 2 6·1 5 15·2

Coronavirus 9 13·6 3 9·1 6 18·2

Parainfluenza 6 9·1 3 9·1 3 9·1

Human metapneumovirus 2 3·0 1 3·0 1 3·0

Influenza 0 0 0 0 0 0

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Supplementary table 2. Prevalence of respiratory virus detection in the first year of life.

The total number of PCR detected viral infections in the first year of life of the subset of samples that we analyzed at age 12 months (A) and 6 years of life (B).

A12 mo samples

(n=145)Placebo(n=66)

Palivizumab(n=79)

Virus n % n % n % P

Any virus 79 54·5 38 57·6 41 51·9 0·93

Multiple viruses 47 32·4 21 31·8 26 32·9 0·53

Respiratory syncytial virus (RSV) 14 9·6 9 13·6 5 6·3 0·24

RSV with any other virus 9 6·2 5 7·6 4 5·1 0·75

Human rhinovirus 66 45·5 28 42·4 38 48·1 0·08

Adenovirus 22 15·2 9 13·6 13 16·5 0·81

Bocavirus 18 12·4 9 13·6 9 11·4 0·88

Coronavirus 17 11·7 7 10·6 10 12·7 0·90

Parainfluenza 16 11·0 4 6·1 12 15·2 0·14

Human metapneumovirus 6 4·1 4 6·1 2 2·5 0·43

Influenza 3 2·1 2 3·0 1 1·3 0·61

B6 year samples

(n=342)Placebo(n=166)

Palivizumab(n=176)

Virus n % n % n % P

Any virus 182 53·2 90 54·2 92 52·3 1·000

Multiple viruses 113 33·0 50 30·1 63 35·8 0·127

Respiratory syncytial virus (RSV) 34 9·9 26 15·7 8 4·5 0·001

RSV with any other virus 22 6·4 15 9·0 7 4·0 0·081

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Human rhinovirus 158 46·2 71 42·8 87 49·4 0·027

Adenovirus 60 17·5 22 13·3 38 21·6 0·063

Bocavirus 52 15·2 24 14·5 28 15·9 0·842

Coronavirus 44 12·9 16 9·6 28 15·9 0·122

Parainfluenza 30 8·8 10 6·0 20 11·4 0·124

Human metapneumovirus 13 3·8 7 4·2 6 3·4 0·906

Influenza 7 2·0 6 3·6 1 0·6 0·066

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Supplementary figure 1. Microbiota profiles during early respiratory infections, at and age 12 months and 6 years.

(A) Bar chart showing average profiles of respiratory samples obtained during early respiratory infections in the first year of life (n=66), and during routine sampling at age 12 months (n=145) and 6 years (n=342). The legend shows the biomarker taxa over time.(B) Hierarchical clustering of all study samples identified 15 profiles. Biomarker species defined by random forests analysis for these 15 profiles identified by hierarchical clustering were from left to right: Chryseobacterium, Klebsiella, Enterococcus faecium, Moraxella osloensis, Streptococcus salivarius, Staphylococcus, Moraxella lincolnii, Streptococcus pneumoniae, Rothia & Streptococcus pneumoniae, Streptococcus pyogenes, Haemophilus, Moraxella lacunata, Corynebacterium propinquum & Dolosigranulum pigrum, M. catarrhalis/nonliquefaciens and Brevundimonas. The figure visualizes from top to bottom the clustering dendrogram, including information on the treatment allocation, sample type, and a bar chart of the relative abundance for each of the biomarker species in the individual samples. A

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Supplementary figure 2. Three-dimensional NMDS plot.

(A) NMDS plots depicting the individual nasopharyngeal microbiota composition at year one (data points, n=145) colored by early life RSV infection: with RSV (purple, n=14) and without RSV (orange, n=132).(B) NMDS biplots depicting the individual nasopharyngeal microbiota composition at year six (data points, n=342) colored by early life RSV infection: with RSV (purple, n=34) and without RSV (orange, n=308). Ellipses represent the standard deviation of all points within a cohort. The stress-value using the first two dimensions was 0·25, whereas this dropped to 0·18 when using three dimensions. Because a stress of <0·2 indicates a reasonable interpretability, 34 we decided to depicts the samples across these three dimensions (NMDS1-NMDS3). The figures also depict the biomarkers species (determined by random forests analysis on hierarchical clustering results) colored by phylum (Green diamonds = Proteobacteria, orange triangles = Firmicutes, purple squares = Actinobacteria, pink circles = Bacteroides).

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Supplementary figure 3. Differential abundance of bacterial taxa between children without and with proven RSV infection.

An analysis similar to that of figure 2b was performed stratifying the cohort at age 6 years alternatively, i.e. the associations between the 20 most differentially abundant taxa and either children with (n=34, left) and without proven RSV (n=308, right) infection early in life. Log 2 fold changes (including 95% confidence intervals) were obtained by metagenomeSeq analysis and corrected for multiple comparisons (Benjamini-Hochberg).

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Supplementary figure 4. Fifty-eight OTUs were identified as contaminants.

The frequency of each OTU is depicted as a function of the bacterial biomass. The dashed black line shows the model of a noncontaminant sequence feature for which frequency is expected to be independent of the input DNA concentration. The red line shows the model of a contaminant sequence feature, for which frequency is expected to be inversely proportional to input DNA concentration, as contaminating DNA will make up a larger fraction of the total DNA in samples with very little total DNA.

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Supplementary figure 5. Samples are distinct from blanks.

(A) The number of sequences in the DNA isolation blanks and PCR blanks (grey) were an order of magnitude lower compared to the samples of children who received either placebo (brown) or palivizumab (green). (B) visualizes the hierarchical clustering dendrogram, which clearly separates the blanks (red) from the samples (grey).

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Supplementary figure 7. Association of the biomarker taxa with age.

Associations between the biomarker taxa and either year one (left) or year six (right). Log 2 fold changes (including 95% confidence intervals) were obtained by metagenomeSeq analysis and corrected for multiple comparisons (Benjamini-Hochberg).

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Supplementary figure 8. Individual microbial developmental trajectories between age one and six.

(A) Visualization of the relation between the overall microbiota profile of the same participant over time as a parallel alluvial diagram. The alluvial diagram depicts the direct links between the microbiota profile at age one (left) and at age six (right). Green lines represent participants that have the same profile at both ages (n=9/118 [7·6%]) and brown lines represent participants that have different profiles at both ages (n=109/118 [92·4%]). Participants with a similar profile at both ages were distributed evenly across treatment groups. (B) In the placebo group, 5/53 (9.4%) participants had the same profile at both ages 48/53 (90·6%) participants had different profiles at both ages. (C) In the palivizumab group, 4/65 (6·2%) participants had the same profile at both ages 61/65 (93·8%) participants had different profiles at both ages.

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Supplementary figure 9. Similarity in total microbiota composition between year one and six.

(A) Boxplots depicting the Bray-Curtis similarities between the microbiota composition at the age of one and six in paired samples of the same child (Within child) or in unpaired samples (Between children). (B) Boxplots depicting the Bray-Curtis similarities between the microbiota composition at the age of one and six in paired samples of the same child stratified for the microbial clusters determined in supplementary figure 1.

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Supplementary 10. Differential abundance of bacterial taxa between treatment groups.

We repeated an identical analysis as in Figure 2, but including the samples of children within the palivizumab group who still developed an RSV infection during their first year of life. Associations between the 20 most differentially abundant taxa and either the palivizumab group (right) or placebo group (left). Log2 fold changes (including 95% confidence intervals) were obtained by metagenomeSeq analysis and corrected for multiple comparisons (Benjamini-Hochberg). (A) depicts the results for samples obtained at 12 months of life, whereas (B) depicts the results for 6 years of life. To avoid OTUs with identical annotations, we refer to OTUs using their taxonomical annotations combined with a rank number based on the abundance of each given OTU.

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