Evidence map›Paper›PMID 25396097›Full record

ArticleCurrent nutrition reports2014

Gene-Lifestyle Interactions in Complex Diseases: Design and Description of the GLACIER and VIKING Studies.

Azra Kurbasic, Alaitz Poveda, Yan Chen, Asa Agren, Elisabeth Engberg, Frank B Hu, Ingegerd Johansson, Ines Barroso, Anders Brändström, Göran Hallmans and 2 more

Abstract read
In one paragraph

Article in Current nutrition reports, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
–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

14 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  14. Impact of a Eukaryotic Translation Initiation Factor 3a Polymorphism on Susceptibility to Gastric Cancer.Medical principles and practice : international journal of the Kuwait University, Health Science Centre
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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

12 authors.

Azra KurbasicDepartment of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, Skåne University Hospital Malmö, CRC, Building 91, Level 10, Jan Waldenströms gata 35, SE-205 02 Malmö, Sweden.
Alaitz PovedaDepartment of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, Skåne University Hospital Malmö, CRC, Building 91, Level 10, Jan Waldenströms gata 35, SE-205 02 Malmö, Sweden.
Yan ChenDepartment of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, Skåne University Hospital Malmö, CRC, Building 91, Level 10, Jan Waldenströms gata 35, SE-205 02 Malmö, Sweden.
Asa AgrenDepartment of Biobank Research, Umeå University, Umeå, Sweden.
Elisabeth EngbergUmeå Demographic Database, Umeå University, Umeå, Sweden.
Frank B HuDepartment of Nutrition, Harvard School of Public Health, Boston, MA, USA.
Ingegerd JohanssonDepartment of Odontology, Umeå University, Umeå, Sweden.
Ines BarrosoWellcome Trust Sanger Institute, Hinxton, Cambridge, UK.
Anders BrändströmUmeå Demographic Database, Umeå University, Umeå, Sweden.
Göran HallmansDepartment of Biobank Research, Umeå University, Umeå, Sweden.
Frida RenströmDepartment of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, Skåne University Hospital Malmö, CRC, Building 91, Level 10, Jan Waldenströms gata 35, SE-205 02 Malmö, Sweden.
Paul W FranksDepartment of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, Skåne University Hospital Malmö, CRC, Building 91, Level 10, Jan Waldenströms gata 35, SE-205 02 Malmö, Sweden.

Funding

Genes and Environment Initiatives in Type 2 DiabetesU01HG004399 · NHGRI · HARVARD SCHOOL OF PUBLIC HEALTH · PI HU, FRANK B · 2007 to 2008
$1.2M
NHGRI NIH HHS U01 HG004399
6 · The paper itself

Abstract

Most complex diseases have well-established genetic and non-genetic risk factors. In some instances, these risk factors are likely to interact, whereby their joint effects convey a level of risk that is either significantly more or less than the sum of these risks. Characterizing these gene-environment interactions may help elucidate the biology of complex diseases, as well as to guide strategies for their targeted prevention. In most cases, the detection of gene-environment interactions will require sample sizes in excess of those needed to detect the marginal effects of the genetic and environmental risk factors. Although many consortia have been formed, comprising multiple diverse cohorts to detect gene-environment interactions, few robust examples of such interactions have been discovered. This may be because combining data across studies, usually through meta-analysis of summary data from the contributing cohorts, is often a statistically inefficient approach for the detection of gene-environment interactions. Ideally, single, very large and well-genotyped prospective cohorts, with validated measures of environmental risk factor and disease outcomes should be used to study interactions. The presence of strong founder effects within those cohorts might further strengthen the capacity to detect novel genetic effects and gene-environment interactions. Access to accurate genealogical data would also aid in studying the diploid nature of the human genome, such as genomic imprinting (parent-of-origin effects). Here we describe two studies from northern Sweden (the GLACIER and VIKING studies) that fulfill these characteristics.

Indexed as

BiobankComplex diseaseGenealogyGeneticsLifestyleScandinavia

Identifiers

PMID25396097
PMCPMC4225623

What OpenQuestion holds

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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.