Evidence map›Paper›PMID 16642434›Full record

ArticleAmerican journal of human genetics2006

Efficient study designs for test of genetic association using sibship data and unrelated cases and controls.

Mingyao Li, Michael Boehnke, Gonçalo R Abecasis

Abstract read
In one paragraph

Article in American journal of human genetics, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 61 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
61citing papers in PubMed, 4 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

61 citing papers in PubMed, 4 syntheses or guidelines pooled it.

  1. Pooled it
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  5. Article
  6. Canine RNF170 Single Base Deletion in a Naturally Occurring Model for Human Neuroaxonal Dystrophy.Movement disorders : official journal of the Movement Disorder Society · 2024
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1 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

3 authors.

Mingyao LiCenter for Clinical Epidemiology and Biostatistics, University of Pennsylvania School of Medicine, Philadelphia; and; Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor. Electronic address: mli@cceb.med.upenn.edu.
Michael BoehnkeDepartment of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor.
Gonçalo R AbecasisDepartment of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor.

Funding

DESIGN AND ANALYSIS OF HUMAN GENE MAPPING STUDIESR01HG000376 · NHGRI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI BOEHNKE, MICHAEL L · 1993 to 2016
$5.5M
Computational and Statistical Models for Human PedigreesR01HG002651 · NHGRI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI ABECASIS, GONCALO · 2003 to 2008
$2.9M
VARIANCE COMPONENTS MODELS FOR MAPPING QTLSR01EY012562 · NEI · UNIVERSITY OF COLORADO AT BOULDER · PI HEWITT, JOHN K · 1999 to 2006
$2.1M
Design and Analysis of Human Gene Mapping StudiesR56HG000376 · NHGRI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI BOEHNKE, MICHAEL L · 2017 to 2017
$400k
DESIGN ISSUES IN GENETIC LINKAGE AND SEGREGATION STUDIESR29HG000376 · NHGRI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI BOEHNKE, MICHAEL · 1990 to 1992
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NEI NIH HHS EY12562NEI NIH HHS R01 EY012562NHGRI NIH HHS HG00376NHGRI NIH HHS HG02651NHGRI NIH HHS R01 HG000376NHGRI NIH HHS R01 HG002651
6 · The paper itself

Abstract

Linkage mapping of complex diseases is often followed by association studies between phenotypes and marker genotypes through use of case-control or family-based designs. Given fixed genotyping resources, it is important to know which study designs are the most efficient. To address this problem, we extended the likelihood-based method of Li et al., which assesses whether there is linkage disequilibrium between a disease locus and a SNP, to accommodate sibships of arbitrary size and disease-phenotype configuration. A key advantage of our method is the ability to combine data from different family structures. We consider scenarios for which genotypes are available for unrelated cases, affected sib pairs (ASPs), or only one sibling per ASP. We construct designs that use cases only and others that use unaffected siblings or unrelated unaffected individuals as controls. Different combinations of cases and controls result in seven study designs. We compare the efficiency of these designs when the number of individuals to be genotyped is fixed. Our results suggest that (1) when the disease is influenced by a single gene, the one sibling per ASP-control design is the most efficient, followed by the ASP-control design, and familial cases contribute more association information than singleton cases; (2) when the disease is influenced by multiple genes, familial cases provide more association information than singleton cases, unless the effect of the locus being tested is much smaller than at least one other untested disease locus; and (3) the case-control design can be useful for detecting genes with small effect in the presence of genes with much larger effect. Our findings will be helpful for researchers designing and analyzing complex disease-association studies and will facilitate genotyping resource allocation.

Indexed as

Case-Control StudiesLinkage DisequilibriumModels, GeneticPolymorphism, Single NucleotideResearch DesignSiblingsChromosome MappingGenetic LinkageGenetic Predisposition to DiseaseGenetics, PopulationLikelihood FunctionsModels, StatisticalPedigreeStatistics, Nonparametric

Identifiers

PMID16642434
PMCPMC1474028

What OpenQuestion holds

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Registered trials

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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.