Evidence map›Paper›PMID 26073768›Full record

ReviewClinical and translational science2015

Precision Genomic Medicine in Cystic Fibrosis.

Eugene H Chang, Joseph Zabner

Abstract readReview
In one paragraph

Review in Clinical and translational science, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–field-weighted citation impact
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

15 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Clinical Phenotypes of Cystic Fibrosis Carriers.Annual review of medicine · 2022
    Review
  5. Article
  6. Review
  7. Article
  8. Article
  9. Review
  10. Article
  11. Cardiovascular Precision Medicine in the Genomics Era.JACC. Basic to translational science · 2018
    Review
  12. Diseases and Molecular Diagnostics: A Step Closer to Precision Medicine.Indian journal of clinical biochemistry : IJCB · 2017
    Article
  13. Review
  14. Review
  15. Article
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

2 authors.

Eugene H ChangDepartment of Otolaryngology-Head and Neck Surgery, The University of Arizona College of Medicine, Tucson, Arizona, USA.
Joseph ZabnerDepartment of Medicine, Roy J. and Lucille A. Carver College of Medicine, University of Iowa, Iowa City, Iowa, USA.

Funding

Vector Core-Core 2P30DK054759 · NIDDK · UNIVERSITY OF IOWA · PI Amy Leanne Ryan · 1998 to 2026
$30.5M
Investigation of CFTR on sinus and craniofacial development in a CF porcine modelK08DE021413 · NIDCR · UNIVERSITY OF IOWA · PI CHANG, EUGENE H · 2011 to 2015
$625k
NIDCR NIH HHS 1K08DE021413-01A1NIDCR NIH HHS K08 DE021413NIDDK NIH HHS P30 DK054759
6 · The paper itself

Abstract

The successful application of precision genomic medicine requires an understanding of how a person's genome can influence his or her disease phenotype and how medical therapies can provide personalized therapy to one's genotype. In this review, we highlight advances in precision genomic medicine in cystic fibrosis (CF), a classic autosomal recessive genetic disorder. We discuss genotype-phenotype correlations in CF, genetic and environmental modifiers of disease, and pharmacogenetic therapies that target specific genetic mutations thereby addressing the primary defect of cystic fibrosis.

Indexed as

Genome, HumanGenomicsMutationPrecision MedicineAnimalsCystic FibrosisCystic Fibrosis Transmembrane Conductance RegulatorDisease ProgressionGene-Environment InteractionGenetic MarkersGenetic Predisposition to DiseaseHumansPhenotypePredictive Value of TestsPrognosisRisk FactorsCFTR protein, humanCystic Fibrosis Transmembrane Conductance RegulatorGenetic Markersepitheliumgenesgenetics

Identifiers

PMID26073768
PMCPMC4626267

What OpenQuestion holds

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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.