Evidence map›Paper›PMID 23999272›Full record

ReviewNature reviews. Genetics2013

Rare-disease genetics in the era of next-generation sequencing: discovery to translation.

Kym M Boycott, Megan R Vanstone, Dennis E Bulman, Alex E MacKenzie

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature reviews. Genetics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 404 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
404citing papers in PubMed, 5 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

404 citing papers in PubMed, 5 syntheses or guidelines pooled it.

  1. Genetically guided precision medicine clinical decision support tools: a systematic review.Journal of the American Medical Informatics Association : JAMIA · 2024
    Pooled it
  2. Pooled it
  3. Recombinant Human Adenovirus-Medicina (Kaunas, Lithuania) · 2021
    Pooled it
  4. Pooled it
  5. Pooled it
  6. Review
  7. Review
  8. Variable Expressiveness of a Novel PathogenicDiseases (Basel, Switzerland) · 2026
    Article
  9. Review
  10. Review
  11. Article
  12. Review
  13. Computational modelling of cell identity.The Biochemical journal · 2026
    Review
  14. Review
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Review

344 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

4 authors.

Kym M BoycottDepartment of Pediatrics, University of Ottawa and Children's Hospital of Eastern Ontario Research Institute, 401 Smyth Road, Ottawa, Ontario K1H 8L1, Canada.
Megan R Vanstone
Dennis E Bulman
Alex E MacKenzie

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Work over the past 25 years has resulted in the identification of genes responsible for ~50% of the estimated 7,000 rare monogenic diseases, and it is predicted that most of the remaining disease-causing genes will be identified by the year 2020, and probably sooner. This marked acceleration is the result of dramatic improvements in DNA-sequencing technologies and the associated analyses. We examine the rapid maturation of rare-disease genetic analysis and successful strategies for gene identification. We highlight the impact of discovering rare-disease-causing genes, from clinical diagnostics to insights gained into biological mechanisms and common diseases. Last, we explore the increasing therapeutic opportunities and challenges that the resulting expansion of the 'atlas' of human genetic pathology will bring.

Indexed as

High-Throughput Nucleotide SequencingGenetic Predisposition to DiseaseGenetics, MedicalGenetic TestingGenome, HumanGenome-Wide Association StudyHumansMutationRare DiseasesSequence Analysis, DNA

Identifiers

PMID23999272

What OpenQuestion holds

Textmetadata
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.