Evidence map›Paper›PMID 32926147›Full record

ArticleThe Journal of infectious diseases2021

Temporal Dysbiosis of Infant Nasal Microbiota Relative to Respiratory Syncytial Virus Infection.

Alex Grier, Ann L Gill, Haeja A Kessler, Anthony Corbett, Sanjukta Bandyopadhyay, James Java, Jeanne Holden-Wiltse, Ann R Falsey, David J Topham, Thomas J Mariani and 3 more

Open access · greenAbstract read
In one paragraph

Article in The Journal of infectious diseases, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 1 pooled it
1.3field-weighted citation impact, top 19% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

21 citing papers in PubMed, 1 synthesis or guideline pooled it, 34 citations in OpenAlex.

  1. Pooled it
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  4. bioRxiv : the preprint server for biology · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors at 1 institution in 1 country.

Alex GrierDepartment of Microbiology and Immunology, University of Rochester School of Medicine and Dentistry, Rochester, New York, USA.
Ann L GillDepartment of Microbiology and Immunology, University of Rochester School of Medicine and Dentistry, Rochester, New York, USA.
Haeja A KesslerDepartment of Microbiology and Immunology, University of Rochester School of Medicine and Dentistry, Rochester, New York, USA.
Anthony CorbettDepartment of Biostatistics and Computational Biology, University of Rochester School of Medicine and Dentistry, Rochester, New York, USA.
Sanjukta BandyopadhyayDepartment of Biostatistics and Computational Biology, University of Rochester School of Medicine and Dentistry, Rochester, New York, USA.
James JavaDepartment of Biostatistics and Computational Biology, University of Rochester School of Medicine and Dentistry, Rochester, New York, USA.
Jeanne Holden-WiltseDepartment of Biostatistics and Computational Biology, University of Rochester School of Medicine and Dentistry, Rochester, New York, USA.
Ann R FalseyDepartment of Medicine, Rochester General Hospital, University of Rochester School of Medicine and Dentistry, Rochester, New York, USA.
David J TophamDepartment of Microbiology and Immunology, University of Rochester School of Medicine and Dentistry, Rochester, New York, USA.
Thomas J MarianiDivision of Neonatology and Pediatric Molecular and Personalized Medicine Program, University of Rochester School of Medicine and Dentistry, Rochester, New York, USA.
Mary T CasertaDivision of Pediatric Infectious Diseases, University of Rochester School of Medicine and Dentistry, Rochester, New York, USA.
Edward E WalshDepartment of Medicine, Rochester General Hospital, University of Rochester School of Medicine and Dentistry, Rochester, New York, USA.
Steven R GillDepartment of Microbiology and Immunology, University of Rochester School of Medicine and Dentistry, Rochester, New York, USA.
University of Rochester · US

Funding

VISUAL INDICES OF NEUROTOXICITYP30ES001247 · NIEHS · UNIVERSITY OF ROCHESTER · PI Martha Susiarjo · 1985 to 2026
$42.8M
NIAID NIH HHS HHSN272201200005CNIEHS NIH HHS P30 ES001247
6 · The paper itself

Abstract

backgroundRespiratory syncytial virus (RSV) is a leading cause of infant respiratory disease. Infant airway microbiota has been associated with respiratory disease risk and severity. The extent to which interactions between RSV and microbiota occur in the airway, and their impact on respiratory disease susceptibility and severity, are unknown.

methodsWe carried out 16S rRNA microbiota profiling of infants in the first year of life from (1) a cross-sectional cohort of 89 RSV-infected infants sampled during illness and 102 matched healthy controls, and (2) a matched longitudinal cohort of 12 infants who developed RSV infection and 12 who did not, sampled before, during, and after infection.

resultsWe identified 12 taxa significantly associated with RSV infection. All 12 taxa were differentially abundant during infection, with 8 associated with disease severity. Nasal microbiota composition was more discriminative of healthy vs infected than of disease severity.

conclusionsOur findings elucidate the chronology of nasal microbiota dysbiosis and suggest an altered developmental trajectory associated with RSV infection. Microbial temporal dynamics reveal indicators of disease risk, correlates of illness and severity, and impact of RSV infection on microbiota composition.

Indexed as

DysbiosisMicrobiotaRespiratory Syncytial Virus InfectionsCross-Sectional StudiesHumansInfantNoseRespiratory Syncytial Virus, HumanRNA, Ribosomal, 16SSeverity of Illness IndexRNA, Ribosomal, 16Sinfant respiratory diseasemicrobiotaRSV

Identifiers

PMID32926147
PMCPMC8136976
OpenAlexW3085268924

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.