Evidence map›Paper›PMID 19597142›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2009

The genetic architecture of Down syndrome phenotypes revealed by high-resolution analysis of human segmental trisomies.

Jan O Korbel, Tal Tirosh-Wagner, Alexander Eckehart Urban, Xiao-Ning Chen, Maya Kasowski, Li Dai, Fabian Grubert, Chandra Erdman, Michael C Gao, Ken Lange and 23 more

Open access · greenAbstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 212 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
212citing papers in PubMed, 2 pooled it
19.0field-weighted citation impact, top 1% 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

212 citing papers in PubMed, 2 syntheses or guidelines pooled it, 396 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Trial
  4. Article
  5. Article
  6. Article
  7. Article
  8. bioRxiv : the preprint server for biology · 2026
    Article
  9. Article
  10. Article
  11. Review
  12. Development of Molecular Neuropathology in Down Syndrome across the Lifespan.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025
    Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Review
  18. Review
  19. Article
  20. Article

152 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

33 authors at 19 institutions in 7 countries.

Jan O KorbelDepartment of Molecular Biophysics and Biochemistry, Yale University School of Medicine, New Haven, CT 06520, USA.
Tal Tirosh-Wagner
Alexander Eckehart Urban
Xiao-Ning Chen
Maya Kasowski
Li Dai
Fabian Grubert
Chandra Erdman
Michael C Gao
Ken Lange
Eric M Sobel
Gillian M Barlow
Arthur S Aylsworth
Nancy J Carpenter
Robin Dawn Clark
Monika Y Cohen
Eric Doran
Tzipora Falik-Zaccai
Susan O Lewin
Ira T Lott
Barbara C McGillivray
John B Moeschler
Mark J Pettenati
Siegfried M Pueschel
Kathleen W Rao
Lisa G Shaffer
Mordechai Shohat
Alexander J Van Riper
Dorothy Warburton
Sherman Weissman
Mark B Gerstein
Michael Snyder
Julie R Korenberg
Cedars-Sinai Medical Center · USYale University · USInstitut thématique Génétique, génomique et bioinformatique · FRUniversity of California, Irvine Medical Center · USUniversity of California, Los Angeles · USUniversity of North Carolina at Chapel Hill · USColumbia University · USDartmouth–Hitchcock Medical Center · USEuropean Bioinformatics Institute · GBInstitute of Macromolecular Chemistry · UAKaiser Permanente · USLoma Linda University · USProvidence College · USSignature Research (United States) · USTel Aviv University · ILUniversity of British Columbia · CAUniversity of Utah · USWake Forest University · USWestern Galilee Hospital · IL

Funding

MEDICAL SCIENTIST TRAINING PROGRAMT32GM007205 · NIGMS · YALE UNIVERSITY · PI KAZMIERCZAK, BARBARA I · 1985 to 2019
$42.9M
NIGMS NIH HHS T32 GM007205
6 · The paper itself

Abstract

Down syndrome (DS), or trisomy 21, is a common disorder associated with several complex clinical phenotypes. Although several hypotheses have been put forward, it is unclear as to whether particular gene loci on chromosome 21 (HSA21) are sufficient to cause DS and its associated features. Here we present a high-resolution genetic map of DS phenotypes based on an analysis of 30 subjects carrying rare segmental trisomies of various regions of HSA21. By using state-of-the-art genomics technologies we mapped segmental trisomies at exon-level resolution and identified discrete regions of 1.8-16.3 Mb likely to be involved in the development of 8 DS phenotypes, 4 of which are congenital malformations, including acute megakaryocytic leukemia, transient myeloproliferative disorder, Hirschsprung disease, duodenal stenosis, imperforate anus, severe mental retardation, DS-Alzheimer Disease, and DS-specific congenital heart disease (DSCHD). Our DS-phenotypic maps located DSCHD to a <2-Mb interval. Furthermore, the map enabled us to present evidence against the necessary involvement of other loci as well as specific hypotheses that have been put forward in relation to the etiology of DS-i.e., the presence of a single DS consensus region and the sufficiency of DSCR1 and DYRK1A, or APP, in causing several severe DS phenotypes. Our study demonstrates the value of combining advanced genomics with cohorts of rare patients for studying DS, a prototype for the role of copy-number variation in complex disease.

Indexed as

Chromosome MappingChromosomes, Human, Pair 21Down SyndromeHumansInfantMeta-Analysis as TopicPhenotypeTrisomy

Identifiers

PMID19597142
PMCPMC2709665
OpenAlexW1964683842

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.