Evidence map›Paper›PMID 19025786›Full record

ArticleGenetic epidemiology2009

Selection of the most informative individuals from families with multiple siblings for association studies.

Chunyu Liu, Qiong Yang, L Adrienne Cupples, James B Meigs, Josée Dupuis

Abstract readComparative StudyEvaluation Study
In one paragraph

Article in Genetic epidemiology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–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

1 citing paper in PubMed.

  1. 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

5 authors.

Chunyu LiuGenetics and Genomics, Biogen Idec, Cambridge, Massachusetts, USA. chunyu.liu@biogenidec.com
Qiong Yang
L Adrienne Cupples
James B Meigs
Josée Dupuis

Funding

Common Genetic Variation and Quantitative Diabetes TraitsR01DK078616 · NIDDK · MASSACHUSETTS GENERAL HOSPITAL · PI MEIGS, JAMES B · 2008 to 2014
$5.0M
Epidemiology of Precursors to Type 2 DiabetesK24DK080140 · NIDDK · MASSACHUSETTS GENERAL HOSPITAL · PI MEIGS, JAMES B · 2007 to 2016
$1.9M
THE FRAMINGHAM HEART STUDY-N01HC25195-268025195-268025195N01HC025195 · HC · TRUSTEES OF BOSTON UNIVERSITY · PI WOLF, PHILIP A · 2002 to 2006
–
NCRR NIH HHS 1S10RR163736-01A1NHLBI NIH HHS N01 HC025195NHLBI NIH HHS N01-HC-25195NIDDK NIH HHS K24 DK080140NIDDK NIH HHS R01 DK078616
6 · The paper itself

Abstract

Association analyses may follow an initial linkage analysis for mapping and identifying genes underlying complex quantitative traits and may be conducted on unrelated subsets of individuals where only one member of a family is included. We evaluate two methods to select one sibling per sibship when multiple siblings are available: (1) one sibling with the most extreme trait value; and (2) one sibling using a combination score statistic based on extreme trait values and identity-by-descent sharing information. We compare the type I error and power. Furthermore, we compare these selection strategies with a strategy that randomly selects one sibling per sibship and with an approach that includes all siblings, using both simulation study and an application to fasting blood glucose in the Framingham Heart Study. When genetic effect is homogeneous, we find that using the combination score can increase power by 30-40% compared to a random selection strategy, and loses only 8-13% of power compared to the full sibship analysis, across all additive models considered, but offers at least 50% genotyping cost saving. In the presence of genetic heterogeneity, the score offers a 50% increase in power over a random selection strategy, but there is substantial loss compared to the full sibship analysis. In application to fasting blood sample, two SNPs are found in common for the selection strategies and the full sample among the 10 highest ranked single nucleotide polymorphisms. The EV strategy tends to agree with the IBD-EV strategy and the analysis of the full sample.

Indexed as

Blood GlucoseChromosome MappingData Interpretation, StatisticalEpidemiologic MethodsFemaleGenetics, PopulationGenome-Wide Association StudyHumansLinkage DisequilibriumMaleModels, GeneticPolymorphism, Single NucleotideQuantitative Trait LociSiblingsBlood Glucose

Identifiers

PMID19025786
PMCPMC3747668

What OpenQuestion holds

Textmetadata
LicenceTDM
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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.