Evidence map›Paper›PMID 21840850›Full record

ArticleGenetics2011

Study designs for identification of rare disease variants in complex diseases: the utility of family-based designs.

Iuliana Ionita-Laza, Ruth Ottman

Open access · bronzeAbstract read
In one paragraph

Article in Genetics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
4.2field-weighted citation impact, top 6% 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

25 citing papers in PubMed, 38 citations in OpenAlex.

  1. Article
  2. Article
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  4. Powerful gene-based testing by integrating long-range chromatin interactions and knockoff genotypes.Proceedings of the National Academy of Sciences of the United States of America · 2021
    Article
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  9. Review
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  14. Review
  15. Article
  16. Identification of novel variants in colorectal cancer families by high-throughput exome sequencing.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2013
    Article
  17. Article
  18. Article
  19. Article
  20. MetaSeq: privacy preserving meta-analysis of sequencing-based association studies.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2013
    Article
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

2 authors at 1 institution in 1 country.

Iuliana Ionita-LazaDepartment of Biostatistics, Columbia University, New York, New York 10032, USA. ii2135@columbia.edu
Ruth Ottman
New York Psychoanalytic Society and Institute · US

Funding

The Epilepsy Phenome/ Genome Project (EPGP)U01NS053998 · NINDS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI LOWENSTEIN, DANIEL H · 2007 to 2013
$26.4M
GENETICS OF AD PARTIAL EPILEPSY WITH AUDITORY FEATURESR01NS036319 · NINDS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI OTTMAN, RUTH · 1997 to 2007
$3.7M
Whole-genome sequencing in multiplex epilepsy familiesRC2NS070344 · NINDS · DUKE UNIVERSITY · PI GOLDSTEIN, DAVID B., OTTMAN, RUTH · 2009 to 2010
$2.0M
Statistical Methods to Assess the role of rare Variants in Complex Traits.R03HG005908 · NHGRI · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI IONITA, IULIANA · 2010 to 2011
$161k
NHGRI NIH HHS R03 HG005908NHGRI NIH HHS R03HG005908-2NINDS NIH HHS R01 NS036319NINDS NIH HHS RC2 NS070344NINDS NIH HHS U01 NS053998
6 · The paper itself

Abstract

The recent progress in sequencing technologies makes possible large-scale medical sequencing efforts to assess the importance of rare variants in complex diseases. The results of such efforts depend heavily on the use of efficient study designs and analytical methods. We introduce here a unified framework for association testing of rare variants in family-based designs or designs based on unselected affected individuals. This framework allows us to quantify the enrichment in rare disease variants in families containing multiple affected individuals and to investigate the optimal design of studies aiming to identify rare disease variants in complex traits. We show that for many complex diseases with small values for the overall sibling recurrence risk ratio, such as Alzheimer's disease and most cancers, sequencing affected individuals with a positive family history of the disease can be extremely advantageous for identifying rare disease variants. In contrast, for complex diseases with large values of the sibling recurrence risk ratio, sequencing unselected affected individuals may be preferable.

Indexed as

PedigreeComputational BiologyDiseaseGenetic LociGenetic Predisposition to DiseaseGenetic VariationHumansPhenotypeRare DiseasesSequence Analysis

Identifiers

PMID21840850
PMCPMC3213373
OpenAlexW1971619969

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.