Evidence map›Paper›PMID 23921533›Full record

SynthesisEuropean journal of human genetics : EJHG2014

Meta-analysis of SNPs involved in variance heterogeneity using Levene's test for equal variances.

Wei Q Deng, Senay Asma, Guillaume Paré

Open access · bronzeAbstract readMeta-Analysis
In one paragraph

Synthesis in European journal of human genetics : EJHG, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
1.2field-weighted citation impact, top 19% 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

5 citing papers in PubMed, 1 synthesis or guideline pooled it, 17 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Review
  5. 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

3 authors at 2 institutions in 1 country.

Wei Q DengPopulation Genomics Program, Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, ON, Canada.
Senay AsmaDepartment of Pathology and Molecular Medicine, McMaster University, Hamilton, ON, Canada.
Guillaume Paré1] Population Genomics Program, Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, ON, Canada [2] Department of Pathology and Molecular Medicine, McMaster University, Hamilton, ON, Canada [3] Population Health Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, ON, Canada [4] Thrombosis and Atherosclerosis Research Institute, Hamilton, ON, Canada.
Population Health Research Institute · CAMcMaster University · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Meta-analysis is a commonly used approach to increase the sample size for genome-wide association searches when individual studies are otherwise underpowered. Here, we present a meta-analysis procedure to estimate the heterogeneity of the quantitative trait variance attributable to genetic variants using Levene's test without needing to exchange individual-level data. The meta-analysis of Levene's test offers the opportunity to combine the considerable sample size of a genome-wide meta-analysis to identify the genetic basis of phenotypic variability and to prioritize single-nucleotide polymorphisms (SNPs) for gene-gene and gene-environment interactions. The use of Levene's test has several advantages, including robustness to departure from the normality assumption, freedom from the influence of the main effects of SNPs, and no assumption of an additive genetic model. We conducted a meta-analysis of the log-transformed body mass index of 5892 individuals and identified a variant with a highly suggestive Levene's test P-value of 4.28E-06 near the NEGR1 locus known to be associated with extreme obesity.

Indexed as

Gene-Environment InteractionGenetic HeterogeneityModels, GeneticPolymorphism, Single NucleotideBody Mass IndexCell Adhesion Molecules, NeuronalData Interpretation, StatisticalEpistasis, GeneticGPI-Linked ProteinsHumansObesityQuantitative Trait LociCell Adhesion Molecules, NeuronalGPI-Linked ProteinsNEGR1 protein, human

Identifiers

PMID23921533
PMCPMC3925287
OpenAlexW2068313148

What OpenQuestion holds

Textmetadata
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.