Evidence map›Paper›PMID 30255819›Full record

ArticleBMC genetics2018

The challenge of detecting genotype-by-methylation interaction: GAW20.

Mariza de Andrade, E Warwick Daw, Aldi T Kraja, Virginia Fisher, Lan Wang, Ke Hu, Jing Li, Razvan Romanescu, Jenna Veenstra, Rui Sun and 2 more

Open access · diamondAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC genetics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact, top 89% 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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
  2. Pancancer Analysis of the Oncogenic and Prognostic Role ofInternational journal of molecular sciences · 2022
    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

12 authors at 7 institutions in 4 countries.

Mariza de AndradeDivision of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, 200 First St. SW, Rochester, MN, 55905, USA. mandrade@mayo.edu.
E Warwick DawDivision of Statistical Genomics, Department of Genetics, Center for Genome Sciences and Systems Biology, Washington University School of Medicine, 660 Euclid Ave, Saint Louis, MO, 63110, USA.
Aldi T KrajaDivision of Statistical Genomics, Department of Genetics, Center for Genome Sciences and Systems Biology, Washington University School of Medicine, 660 Euclid Ave, Saint Louis, MO, 63110, USA.
Virginia FisherDepartment of Biostatistics, Boston University School of Public Health, Boston, 715 Albany St, Boston, MA, 02118, USA.
Lan WangDepartment of Biostatistics, Boston University School of Public Health, Boston, 715 Albany St, Boston, MA, 02118, USA.
Ke HuDepartment of Electrical Engineering and Computer Science, Case Western Reserve University, 10900 Euclid Ave, Cleveland, OH, 44106, USA.
Jing LiDepartment of Electrical Engineering and Computer Science, Case Western Reserve University, 10900 Euclid Ave, Cleveland, OH, 44106, USA.
Razvan RomanescuLunenfeld-Tanenbaum Research Institute, Sinai Health System, University of Toronto, 600 University Ave, Toronto, ON, M5G 1X5, Canada.
Jenna VeenstraDepartment of Biology, Dordt College, 498 4th Ave. NE, Sioux Center, IA, 51250, USA.
Rui SunDivision of Biostatistics, Centre for Clinical Research and Biostatistics, JC School of Public Health and Primary Care, the Chinese University of Hong Kong, Shatin, N.T, Hong Kong, SAR, China.
Haoyi WengDivision of Biostatistics, Centre for Clinical Research and Biostatistics, JC School of Public Health and Primary Care, the Chinese University of Hong Kong, Shatin, N.T, Hong Kong, SAR, China.
Wenda ZhouDepartment of Statistics, Columbia University, 1255 Amsterdam Avenue, New York, NY, 10027, USA.
Boston University · USCase Western Reserve University · USCity University of Hong Kong, Shenzhen Research Institute · CNColumbia University · USDordt University · USMayo Clinic · USUniversity of Toronto · CA

Funding

Genetic and Environmental Determinants of TriglyceridesU01HL072524 · NHLBI · UNIVERSITY OF MINNESOTA TWIN CITIES · PI ARNETT, DONNA K · 2002 to 2008
$11.9M
GENETIC ANALYSIS OF COMMON DISEASES: AN EVALUATIONR01GM031575 · NIGMS · UNIVERSITY OF TEXAS RIO GRANDE VALLEY · PI ALMASY, LAURA A. · 1985 to 2016
$7.8M
Genomewide Association Study of Lipid Response to Fenofibrate and Dietary FatR01HL091357 · NHLBI · UNIVERSITY OF KENTUCKY · PI ARNETT, DONNA K · 2008 to 2018
$5.8M
Epigenetic Determinants of Lipid Response to Dietary Fat and FenofibrateR01HL104135 · NHLBI · UNIVERSITY OF KENTUCKY · PI ARNETT, DONNA K · 2010 to 2015
$5.5M
Inheritance Inference in Large Pedigrees Using the Spectral Clustering Algorithm and ApplicationsR03HG008632 · NHGRI · CASE WESTERN RESERVE UNIVERSITY · PI LI, JING · 2016 to 2017
$143k
NHGRI NIH HHS R03 HG008632NHLBI NIH HHS R01 HL091357NHLBI NIH HHS R01 HL104135NHLBI NIH HHS U01 HL072524NIGMS NIH HHS R01 GM031575
6 · The paper itself

Abstract

backgroundGAW20 working group 5 brought together researchers who contributed 7 papers with the aim of evaluating methods to detect genetic by epigenetic interactions. GAW20 distributed real data from the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) study, including single-nucleotide polymorphism (SNP) markers, methylation (cytosine-phosphate-guanine [CpG]) markers, and phenotype information on up to 995 individuals. In addition, a simulated data set based on the real data was provided.

resultsThe 7 contributed papers analyzed these data sets with a number of different statistical methods, including generalized linear mixed models, mediation analysis, machine learning, W-test, and sparsity-inducing regularized regression. These methods generally appeared to perform well. Several papers confirmed a number of causative SNPs in either the large number of simulation sets or the real data on chromosome 11. Findings were also reported for different SNPs, CpG sites, and SNP-CpG site interaction pairs.

conclusionsIn the simulation (200 replications), power appeared generally good for large interaction effects, but smaller effects will require larger studies or consortium collaboration for realizing a sufficient power.

Indexed as

DNA MethylationGenome-Wide Association StudyCpG IslandsGenotypeHumansHypertriglyceridemiaHypoglycemic AgentsMachine LearningPolymorphism, Single NucleotideHypoglycemic AgentsAdaptive W-testCandidate gene associationGenome wide associationInteractionLASSOMediation analysisMethylationMulti-level Gaussian modelRegion based associationRegression and random forest trees

Identifiers

PMID30255819
PMCPMC6157121
OpenAlexW2891680926

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.