Evidence mapPaperPMID 26809563Full record

ReviewCurrent environmental health reports2016

Analytical Complexity in Detection of Gene Variant-by-Environment Exposure Interactions in High-Throughput Genomic and Exposomic Research.

Chirag J Patel

Abstract readReview
In one paragraph

Review in Current environmental health reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Review
  2. Opportunities for Gene and Environment Research in Cancer: An Updated Review of NCI's Extramural Grant Portfolio.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2021
    Review
  3. Review
  4. Personalized medicine-concepts, technologies, and applications in inflammatory skin diseases.APMIS : acta pathologica, microbiologica, et immunologica Scandinavica · 2019
    Review
  5. Article
  6. Article
  7. Opportunities and Challenges for Environmental Exposure Assessment in Population-Based Studies.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2017
    Review
  8. Review
  9. Article
  10. Review
  11. 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

1 author.

Chirag J PatelDepartment of Biomedical Informatics, Harvard Medical School, 10 Shattuck St., Boston, MA, 02215, USA. chirag_patel@hms.harvard.edu.

Funding

NIEHS NIH HHS K99 ES023504NIEHS NIH HHS K99ES023504NIEHS NIH HHS R00 ES023504NIEHS NIH HHS R21 ES025052NIEHS NIH HHS R21ES25052
6 · The paper itself

Abstract

It seems intuitive that disease risk is influenced by the interaction between inherited genetic variants and environmental exposure factors; however, we have few documented interactions between variants and exposures. Advances in technology may enable the simultaneous measurement (i.e., on the same individuals in an epidemiological study) of millions of genome variants with thousands of environmental "exposome" factors, significantly increasing the number of possible factor pairs available for testing for the presence of interactions. The burden of analytic complexity, or sheer number of genetic and exposure factors measured, poses a considerable challenge for discovery of interactions in population-scale data. Advances in analytic approaches, large sample sizes, less conservative methods to mitigate multiple testing, and strong biological priors will be required to prune the search space to find reproducible and robust gene-by-environment interactions in observational data.

Indexed as

Gene-Environment InteractionGenetic VariationEnvironmental ExposureGenome-Wide Association StudyHumansEnvironment-wide association studyExposomeGene-by-environment interactionGenomeGenome-wide association study

Identifiers

PMID26809563
PMCPMC4789192

What Socratic 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 Socratic graph.