Evidence map›Paper›PMID 22740241›Full record

ArticleGenetic epidemiology2012

Analysis of genetic interactions involving maternal and offspring genotypes at different Loci: power simulation and application to testicular cancer.

Jérémie Nsengimana, Jennifer H Barrett

Open access · bronzeAbstract read
In one paragraph

Article in Genetic epidemiology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact, top 94% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. 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 at 1 institution in 1 country.

Jérémie NsengimanaSection of Epidemiology and Biostatistics, Leeds Institute of Molecular Medicine, University of Leeds, Leeds, United Kingdom. J.Nsengimana@leeds.ac.uk
Jennifer H Barrett
University of Leeds · GB

Funding

Cancer Research UK 10589Cancer Research UK C588/A4994
6 · The paper itself

Abstract

The analyses of genetic interaction between maternal and offspring genotypes are usually conducted considering a single locus. Here, we propose testing maternal × offspring (M×O) and maternal × maternal (M×M) genotype interactions involving two unlinked loci. We reformulate the log-linear approach of analyzing cases and their parents (family trios) to accommodate two loci, fit fuller models to avoid confounding in a first analysis step and propose that the model be reduced to the most prominent effects in a second step. We conduct extensive simulations to assess the validity and power of this approach under various model assumptions. We show that the approach is valid and has good power to detect M×O and M×M interactions. For example, the power to detect a dominant interaction relative risk of 1.5 (both M×O and M×M) is 70% with 300 trios and approaches 100% with 1,000 trios. Unlike the main effects, M×O and M×M interactions are conditionally independent of mating types, and consequently, their power is not affected by missing paternal genotypes. When applied to single-locus M×O interaction, our method is as powerful as other existing methods. Applying the method to testicular cancer, we found a nominally significant M×M interaction between single nucleotide polymorphisms from C-Kit Ligand (KITLG) and Sex Hormone Binding Globulin (SHBG) using 210 families (relative risk 2.2, P = 0.03). This finding supports a role of maternal hormones in offspring testicular cancer and warrants confirmation in a larger dataset.

Indexed as

Genetic Predisposition to DiseaseModels, GeneticAlgorithmsFemaleGenotypeHumansLinear ModelsMaleParentsPolymorphism, Single NucleotideReproducibility of ResultsSex Hormone-Binding GlobulinStem Cell FactorTesticular NeoplasmsSex Hormone-Binding GlobulinStem Cell Factor

Identifiers

PMID22740241
PMCPMC3504980
OpenAlexW1823052056

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

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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.