Evidence map›Paper›PMID 20106545›Full record

ReviewTrends in genetics : TIG2010

Beyond genome-wide association studies: genetic heterogeneity and individual predisposition to cancer.

Antonella Galvan, John P A Ioannidis, Tommaso A Dragani

Abstract readReview
In one paragraph

Review in Trends in genetics : TIG, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 88 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
88citing 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

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

  1. The Shared Genetic Architectures Between Lung Cancer and Multiple Polygenic Phenotypes in Genome-Wide Association Studies.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2021
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  20. Clonal Evolution ofCells · 2019
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28 more citing papers are in PubMed but not listed here.

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.

Antonella GalvanDepartment of Predictive and for Prevention Medicine, Fondazione IRCCS, Istituto Nazionale Tumori, Via G. Venezian 1, 20133 Milan, Italy.
John P A Ioannidis
Tommaso A Dragani

Funding

TUFTS CLINICAL AND TRANSLATION SCIENCE INSTITUTE (UL1): BPCAUL1RR025752 · NCRR · TUFTS UNIVERSITY BOSTON · PI SELKER, HARRY P. · 2008 to 2011
$17.6M
NCRR NIH HHS UL1 RR025752
6 · The paper itself

Abstract

Genome-wide association studies (GWAS) using population-based designs have identified many genetic loci associated with risk of a range of complex diseases including cancer; however, each locus exerts a very small effect and most heritability remains unexplained. Family-based pedigree studies have also suggested tentative loci linked to increased cancer risk, often characterized by pedigree-specificity. However, comparison between the results of population- and family-based studies shows little concordance. Explanations for this unidentified genetic 'dark matter' of cancer include phenotype ascertainment issues, limited power, gene-gene and gene-environment interactions, population heterogeneity, parent-of-origin-specific effects, and rare and unexplored variants. Many of these reasons converge towards the concept of genetic heterogeneity that might implicate hundreds of genetic variants in regulating cancer risk. Dissecting the dark matter is a challenging task. Further insights can be gained from both population association and pedigree studies.

Indexed as

Genetic HeterogeneityGenetic Predisposition to DiseaseGenetics, PopulationGenome-Wide Association StudyHumansNeoplasmsRisk Factors

Identifiers

PMID20106545
PMCPMC2826571

What OpenQuestion holds

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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.