Evidence map›Paper›PMID 31910864›Full record

ArticleGenome biology2020

Non-coding RNAs underlie genetic predisposition to breast cancer.

Mahdi Moradi Marjaneh, Jonathan Beesley, Tracy A O'Mara, Pamela Mukhopadhyay, Lambros T Koufariotis, Stephen Kazakoff, Nehal Hussein, Laura Fachal, Nenad Bartonicek, Kristine M Hillman and 16 more

Open access · goldAbstract read
In one paragraph

Article in Genome biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
4.1field-weighted citation impact, top 4% 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

19 citing papers in PubMed, 47 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Dysanapsis Genetic Risk Predicts Lung Function Across the Lifespan.American journal of respiratory and critical care medicine · 2024
    Article
  6. Article
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  12. Review
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  14. Article
  15. The Role of lncRNA in the Development of Tumors, including Breast Cancer.International journal of molecular sciences · 2021
    Review
  16. The Functional Hallmarks of Cancer Predisposition Genes.Cancer management and research · 2021
    Review
  17. Article
  18. Review
  19. 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

26 authors at 4 institutions in 2 countries.

Mahdi Moradi MarjanehCancer Division, QIMR Berghofer Medical Research Institute, Brisbane, Australia.
Jonathan BeesleyCancer Division, QIMR Berghofer Medical Research Institute, Brisbane, Australia.
Tracy A O'MaraCancer Division, QIMR Berghofer Medical Research Institute, Brisbane, Australia.
Pamela MukhopadhyayCancer Division, QIMR Berghofer Medical Research Institute, Brisbane, Australia.
Lambros T KoufariotisCancer Division, QIMR Berghofer Medical Research Institute, Brisbane, Australia.
Stephen KazakoffCancer Division, QIMR Berghofer Medical Research Institute, Brisbane, Australia.
Nehal HusseinCancer Division, QIMR Berghofer Medical Research Institute, Brisbane, Australia.
Laura FachalCentre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK.
Nenad BartonicekGarvan Institute of Medical Research, Sydney, Australia.
Kristine M HillmanCancer Division, QIMR Berghofer Medical Research Institute, Brisbane, Australia.
Susanne KaufmannCancer Division, QIMR Berghofer Medical Research Institute, Brisbane, Australia.
Haran SivakumaranCancer Division, QIMR Berghofer Medical Research Institute, Brisbane, Australia.
Chanel E SmartUQ Centre for Clinical Research, Faculty of Medicine, The University of Queensland, Brisbane, Australia.
Amy E McCart ReedUQ Centre for Clinical Research, Faculty of Medicine, The University of Queensland, Brisbane, Australia.
Kaltin FergusonUQ Centre for Clinical Research, Faculty of Medicine, The University of Queensland, Brisbane, Australia.
Jodi M SaunusUQ Centre for Clinical Research, Faculty of Medicine, The University of Queensland, Brisbane, Australia.
Sunil R LakhaniUQ Centre for Clinical Research, Faculty of Medicine, The University of Queensland, Brisbane, Australia.
Daniel R BarnesCentre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
Antonis C AntoniouCentre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
Marcel E DingerGarvan Institute of Medical Research, Sydney, Australia.
Nicola WaddellCancer Division, QIMR Berghofer Medical Research Institute, Brisbane, Australia.
Douglas F EastonCentre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK.
Alison M DunningCentre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK.
Georgia Chenevix-TrenchCancer Division, QIMR Berghofer Medical Research Institute, Brisbane, Australia.
Stacey L EdwardsCancer Division, QIMR Berghofer Medical Research Institute, Brisbane, Australia. Stacey.Edwards@qimrberghofer.edu.au.
Juliet D FrenchCancer Division, QIMR Berghofer Medical Research Institute, Brisbane, Australia. Juliet.French@qimrberghofer.edu.au.ORCID 0000-0002-9770-0198
QIMR Berghofer Medical Research Institute · AUThe University of Queensland · AUUniversity of Cambridge · GBGarvan Institute of Medical Research · AU

Funding

Cancer Research UK 20861
6 · The paper itself

Abstract

backgroundGenetic variants identified through genome-wide association studies (GWAS) are predominantly non-coding and typically attributed to altered regulatory elements such as enhancers and promoters. However, the contribution of non-coding RNAs to complex traits is not clear.

resultsUsing targeted RNA sequencing, we systematically annotated multi-exonic non-coding RNA (mencRNA) genes transcribed from 1.5-Mb intervals surrounding 139 breast cancer GWAS signals and assessed their contribution to breast cancer risk. We identify more than 4000 mencRNA genes and show their expression distinguishes normal breast tissue from tumors and different breast cancer subtypes. Importantly, breast cancer risk variants, identified through genetic fine-mapping, are significantly enriched in mencRNA exons, but not the promoters or introns. eQTL analyses identify mencRNAs whose expression is associated with risk variants. Furthermore, chromatin interaction data identify hundreds of mencRNA promoters that loop to regions that contain breast cancer risk variants.

conclusionsWe have compiled the largest catalog of breast cancer-associated mencRNAs to date and provide evidence that modulation of mencRNAs by GWAS variants may provide an alternative mechanism underlying complex traits.

Indexed as

Breast NeoplasmsGenome-Wide Association StudyHumansRNA, UntranslatedSequence Analysis, RNARNA, Untranslated

Identifiers

PMID31910864
PMCPMC6947989
OpenAlexW2995513473

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.