Evidence map›Paper›PMID 30631320›Full record

ReviewFrontiers in immunology2018

Leveraging Multilayered "Omics" Data for Atopic Dermatitis: A Road Map to Precision Medicine.

Debajyoti Ghosh, Jonathan A Bernstein, Gurjit K Khurana Hershey, Marc E Rothenberg, Tesfaye B Mersha

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in immunology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 54 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
54citing papers in PubMed, 1 pooled it
9.4field-weighted citation impact, top 2% 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

54 citing papers in PubMed, 1 synthesis or guideline pooled it, 118 citations in OpenAlex.

  1. Pooled it
  2. Observational
  3. Review
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  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Prediction of pediatric peanut oral food challenge outcomes using machine learning.The journal of allergy and clinical immunology. Global · 2024
    Article
  11. Article
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  13. From Mendel to multi-omics: shifting paradigms.European journal of human genetics : EJHG · 2024
    Article
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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

5 authors at 2 institutions in 1 country.

Debajyoti GhoshDivision of Immunology, Allergy & Rheumatology, Department of Internal Medicine, University of Cincinnati, Cincinnati, OH, United States.
Jonathan A BernsteinDivision of Immunology, Allergy & Rheumatology, Department of Internal Medicine, University of Cincinnati, Cincinnati, OH, United States.
Gurjit K Khurana HersheyDivision of Asthma Research, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati, Cincinnati, OH, United States.
Marc E RothenbergDivision of Allergy and Immunology, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati, Cincinnati, OH, United States.
Tesfaye B MershaDivision of Asthma Research, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati, Cincinnati, OH, United States.
University of Cincinnati · USCincinnati Children's Hospital Medical Center · US

Funding

Unraveling ancestry and environmental exposure interactions in childhood asthmaR01HL132344 · NHLBI · CINCINNATI CHILDRENS HOSP MED CTR · PI MERSHA, TESFAYE B. · 2016 to 2020
$3.4M
NHLBI NIH HHS R01 HL132344
6 · The paper itself

Abstract

Atopic dermatitis (AD) is a complex multifactorial inflammatory skin disease that affects ~280 million people worldwide. About 85% of AD cases begin in childhood, a significant portion of which can persist into adulthood. Moreover, a typical progression of children with AD to food allergy, asthma or allergic rhinitis has been reported ("allergic march" or "atopic march"). AD comprises highly heterogeneous sub-phenotypes/endotypes resulting from complex interplay between intrinsic and extrinsic factors, such as environmental stimuli, and genetic factors regulating cutaneous functions (impaired barrier function, epidermal lipid, and protease abnormalities), immune functions and the microbiome. Though the roles of high-throughput "omics" integrations in defining endotypes are recognized, current analyses are primarily based on individual omics data and using binary clinical outcomes. Although individual omics analysis, such as genome-wide association studies (GWAS), can effectively map variants correlated with AD, the majority of the heritability and the functional relevance of discovered variants are not explained or known by the identified variants. The limited success of singular approaches underscores the need for holistic and integrated approaches to investigate complex phenotypes using trans-omics data integration strategies. Integrating omics layers (e.g., genome, epigenome, transcriptome, proteome, metabolome, lipidome, exposome, microbiome), which often have complementary and synergistic effects, might provide the opportunity to capture the flow of information underlying AD disease manifestation. Overlapping genes/candidates derived from multiple omics types include

Indexed as

Dermatitis, AtopicGenome-Wide Association StudyPrecision MedicineAnimalsFilaggrin ProteinsGenomicsHumansMetabolomicsFilaggrin Proteinsatopic dermatitisbioinformaticsbiomarkersendotypesmachine learningmulti-omics integrationnetwork analysisomics

Identifiers

PMID30631320
PMCPMC6315155
OpenAlexW2905330547

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.