Evidence map›Paper›PMID 30634949›Full record

ArticleBMC medical genetics2019

Modeling gene-environment interactions in longitudinal family studies: a comparison of methods and their application to the association between the IGF pathway and childhood obesity.

Cheng Wang, Marie-Hélène Roy-Gagnon, Jean-François Lefebvre, Kelly M Burkett, Lise Dubois

Open access · goldAbstract readTwin Study
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC medical genetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
0.7field-weighted citation impact, top 25% 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

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

  1. Pooled it
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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 1 institution in 1 country.

Cheng WangSchool of Epidemiology and Public Health, University of Ottawa, 600 Peter Morand Cres, Ottawa, Ontario, K1G 5Z3, Canada.
Marie-Hélène Roy-GagnonSchool of Epidemiology and Public Health, University of Ottawa, 600 Peter Morand Cres, Ottawa, Ontario, K1G 5Z3, Canada.
Jean-François LefebvreSchool of Epidemiology and Public Health, University of Ottawa, 600 Peter Morand Cres, Ottawa, Ontario, K1G 5Z3, Canada.
Kelly M BurkettDepartment of Mathematics and Statistics, University of Ottawa, 150 Louis-Pasteur Pvt, Ottawa, Ontario, K1N 6N5, Canada. kburkett@uottawa.ca.ORCID 0000-0002-9488-5588
Lise DuboisSchool of Epidemiology and Public Health, University of Ottawa, 600 Peter Morand Cres, Ottawa, Ontario, K1G 5Z3, Canada.
University of Ottawa · CA

Funding

CIHR
6 · The paper itself

Abstract

backgroundThe interactive effect of the IGF pathway genes with the environment may contribute to childhood obesity. Such gene-environment interactions can take on complex forms. Detecting those relationships using longitudinal family studies requires simultaneously accounting for correlations within individuals and families.

methodsWe studied three methods for detecting interaction effects in longitudinal family studies. The twin model and the nonparametric partition-based score test utilized individual outcome averages, whereas the linear mixed model used all available longitudinal data points. Simulation experiments were performed to evaluate the methods' power to detect different gene-environment interaction relationships. These methods were applied to the Quebec Newborn Twin Study data to test for interaction effects between the IGF pathway genes (IGF-1, IGFALS) and environmental factors (physical activity, daycare attendance and sleep duration) on body mass index outcomes.

resultsFor the simulated data, the twin model with the mean time summary statistic yielded good performance overall. Modelling an interaction as linear when the true model had a different relationship influenced power; for certain non-linear interactions, none of the three methods were effective. Our analysis of the IGF pathway genes showed suggestive association for the joint effect of IGF-1 variant at position 102,791,894 of chromosome 12 and physical activity. However, this association was not statistically significant after multiple testing correction.

conclusionsThe analytical approaches considered in this study were not robust to different gene-environment interactions. Methodological innovations are needed to improve the current methods' performances for detecting non-linear interactions. More studies are needed in order to better understand the IGF pathway's role in childhood obesity development.

Indexed as

Gene-Environment InteractionBody Mass IndexCarrier ProteinsChildChild, PreschoolChromosomes, Human, Pair 12FemaleFollow-Up StudiesGlycoproteinsHumansInfantInfant, NewbornInsulin-Like Growth Factor ILinear ModelsLongitudinal StudiesMaleCarrier ProteinsGlycoproteinsIGF1 protein, humaninsulin-like growth factor binding protein, acid labile subunitInsulin-Like Growth Factor IChildhood obesityGene-environment interactionInsulin-like growth factorsLongitudinal family studiesNon-linear interactionSimulation studiesTwin studies

Identifiers

PMID30634949
PMCPMC6329142
OpenAlexW2911675923

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LicenceCC BY
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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.