Evidence map›Paper›PMID 27848153›Full record

ArticleBreast cancer research and treatment2017

Previous GWAS hits in relation to young-onset breast cancer.

Min Shi, Katie M O'Brien, Dale P Sandler, Jack A Taylor, Dmitri V Zaykin, Clarice R Weinberg

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Breast cancer research and treatment, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.8field-weighted citation impact, top 12% 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

6 citing papers in PubMed, 12 citations in OpenAlex.

  1. Article
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  5. Article
  6. Fibroblast Growth Factor Receptor 2 Signaling in Breast Cancer.International journal of biological sciences · 2017
    Review
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

6 authors at 1 institution in 1 country.

Min ShiBiostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, 111 TW Alexander Dr, Research Triangle Park, Durham, NC, 27709, USA.
Katie M O'BrienBiostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, 111 TW Alexander Dr, Research Triangle Park, Durham, NC, 27709, USA.
Dale P SandlerEpidemiology Branch, National Institute of Environmental Health Sciences, 111 TW Alexander Fr, Research Triangle Park, Durham, NC, 27709, USA.
Jack A TaylorEpidemiology Branch, National Institute of Environmental Health Sciences, 111 TW Alexander Fr, Research Triangle Park, Durham, NC, 27709, USA.
Dmitri V ZaykinBiostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, 111 TW Alexander Dr, Research Triangle Park, Durham, NC, 27709, USA.
Clarice R WeinbergBiostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, 111 TW Alexander Dr, Research Triangle Park, Durham, NC, 27709, USA. weinber2@niehs.nih.gov.
National Institute of Environmental Health Sciences · US

Funding

Environmental and Genetic Risk Factors For Breast Cancer: The Sister StudyZIAES044005 · NIEHS · NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES · PI SANDLER, DALE P · 2009 to 2025
$22.7M
The Two Sister StudyZIAES102245 · NIEHS · NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES · PI WEINBERG, CLARICE · 2009 to 2025
$8.6M
Statistical, population genetics and genetic epidemiologyZIAES101866 · NIEHS · NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES · PI ZAYKIN, DMITRI V · 2009 to 2021
$5.8M
Genetic and Environmental Risk Factors for Breast Cancer: The Sister StudyZ01ES044005 · NIEHS · NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES · PI SANDLER, DALE P · 1999 to 2008
$1.3M
The Two Sister StudyZ01ES102245 · NIEHS · NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES · PI WEINBERG, CLARICE · 2008 to 2008
$84k
Intramural NIH HHS Z01 ES044005Intramural NIH HHS Z01 ES102245Intramural NIH HHS Z99 ES999999Intramural NIH HHS ZIA ES044005Intramural NIH HHS ZIA ES102245
6 · The paper itself

Abstract

purposeGenome-wide association studies (GWAS) have identified dozens of single-nucleotide polymorphisms (SNPs) associated with breast cancer. Few studies focused on young-onset breast cancer, which exhibits etiologic and tumor-type differences from older-onset disease. Possible confounding by prenatal effects of the maternal genome has also not been considered.

methodsUsing a family-based design for breast cancer before age 50, we assessed the relationship between breast cancer and 77 GWAS-identified breast cancer risk SNPs. We estimated relative risks (RR) for inherited and maternally mediated genetic effects. We also used published RR estimates to calculate genetic risk scores and model joint effects.

resultsSeventeen of the candidate SNPs were nominally associated with young-onset breast cancer in our 1296 non-Hispanic white affected families (uncorrected p value <0.05). Top-ranked SNPs included rs3803662-A (TOX3, RR = 1.39; p = 7.0 × 10

conclusionsThe results of this family-based study indicate that no effects of previously identified risk SNPs were explained by prenatal effects of maternal variants. Many of the known breast cancer risk variants were associated with young-onset breast cancer, with evidence that TOX3, ESR1, FGFR2, and RAD51B are important for young-onset disease.

Indexed as

Genetic Predisposition to DiseaseGenome-Wide Association StudyAdultAge of OnsetAllelesBreast NeoplasmsEthnicityFemaleGenotypeHumansMiddle AgedOdds RatioPolymorphism, Single NucleotideRisk AssessmentRisk FactorsYoung AdultFamily-based genetic methodsGenetic risk scoreGenome-wide association studyLog-linear modelsSingle-nucleotide polymorphismYoung-onset breast cancer

Identifiers

PMID27848153
PMCPMC5226879
OpenAlexW2556316003

What Socratic holds

Textmetadata
LicenceTDM
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 Socratic graph.