Evidence map›Paper›PMID 35718139›Full record

ArticleThe Journal of allergy and clinical immunology2022

Examination of host genetic effects on nasal microbiome composition.

Haritz Irizar, Yoojin Chun, Zoe Arditi, Anh Do, Galina Grishina, Alexander Grishin, Alfin Vicencio, Supinda Bunyavanich

Open access · bronzeAbstract read
In one paragraph

Article in The Journal of allergy and clinical immunology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
0.8field-weighted citation impact, top 31% 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

8 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Article
  3. Microbial influencers: the airway microbiome's role in asthma.The Journal of clinical investigation · 2025
    Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Recent progress in the genetic and epigenetic underpinnings of atopy.The Journal of allergy and clinical immunology · 2023
    Review
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

8 authors at 1 institution in 1 country.

Haritz IrizarDepartment of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY.
Yoojin ChunDepartment of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY.
Zoe ArditiDepartment of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY.
Anh DoDepartment of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY.
Galina GrishinaDepartment of Pediatrics, Icahn School of Medicine at Mount Sinai, New York, NY.
Alexander GrishinDepartment of Pediatrics, Icahn School of Medicine at Mount Sinai, New York, NY.
Alfin VicencioDepartment of Pediatrics, Icahn School of Medicine at Mount Sinai, New York, NY.
Supinda BunyavanichDepartment of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY; Department of Pediatrics, Icahn School of Medicine at Mount Sinai, New York, NY. Electronic address: supinda@post.harvard.edu.
Icahn School of Medicine at Mount Sinai · US

Funding

Nasal biomarkers of asthmaR01AI118833 · NIAID · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI BUNYAVANICH, SUPINDA · 2015 to 2019
$3.8M
NIAID NIH HHS R01 AI118833
6 · The paper itself

Abstract

backgroundGenetic predisposition increases risk for asthma, and distinct nasal microbial compositions are associated with asthma. Host genetics might shape nasal microbiome composition.

objectiveWe examined associations between host genetics and nasal microbiome composition.

methodsNasal samples were collected from 584 participants from the Mount Sinai Health System, New York. Seventy-seven follow-up samples were collected from a subset of 40 participants. 16S rRNA sequencing and RNA sequencing were performed on nasal samples. Beta diversity was calculated, variant calling on RNA sequencing data was performed, and genetic relatedness between individuals was determined. Using linear regression models, we tested for associations between genetic relatedness and nasal microbiome composition.

resultsThe median age of the cohort was 14.6 (interquartile range 11.2-19.5) years, with participants representing diverse ancestries and 52.7% of the cohort being female. For participants who provided follow-up samples, the median time between samples was 5.1 (interquartile range 1.4-7.2) months. Nasal microbiome composition similarity as reflected by beta diversity was significantly higher within subjects over time versus between subjects (coefficient = 0.091, P = 2.84

conclusionHost genetics has little influence on nasal microbiome composition.

Indexed as

AsthmaMicrobiotaAdolescentAdultChildCohort StudiesFemaleHumansMaleNoseRNA, Ribosomal, 16SYoung AdultRNA, Ribosomal, 16Sbeta diversitygenetic relatednessheritabilityhost geneticsNasal microbiome

Identifiers

PMID35718139
PMCPMC9643606
OpenAlexW4282982851

What OpenQuestion holds

Textmetadata
LicenceTDM
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.