Genetic Epidemiology, Translational Neurogenomics, Psychiatric Genetics and Statistical Genetics Laboratories investigate the pattern of disease in families, particularly identical and non-identical twins, to assess the relative importance of genes and environment in a variety of important health problems.
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PMID
18183040
TITLE
Genome-wide association studies of quantitative traits with related individuals: little (power) lost but much to be gained.
ABSTRACT
For complex disease genetics research in human populations, remarkable progress has been made in recent times with the publication of a number of genome-wide association scans (GWAS) and subsequent statistical replications. These studies have identified new genes and pathways implicated in disease, many of which were not known before. Given these early successes, more GWAS are being conducted and planned, both for disease and quantitative phenotypes. Many researchers and clinicians have DNA samples available on collections of families, including both cases and controls. Twin registries around the world have facilitated the collection of large numbers of families, with DNA and multiple quantitative phenotypes collected on twin pairs and their relatives. In the design of a new GWAS with a fixed budget for the number of chips, the question arises whether to include or exclude related individuals. It is commonly believed to be preferable to use unrelated individuals in the first stage of a GWAS because relatives are 'over-matched' for genotypes. In this study, we quantify that for GWAS of a quantitative phenotype, relative to a sample of unrelated individuals surprisingly little power is lost when using relatives. The advantages of using relatives are manifold, including the ability to perform more quality control, the choice to perform within-family tests of association that are robust to population stratification, and the ability to perform joint linkage and association analysis. Therefore, the advantages of using relatives in GWAS for quantitative traits may well outweigh the small disadvantage in terms of statistical power.
DATE PUBLISHED
2008 Mar
HISTORY
PUBSTATUS PUBSTATUSDATE
aheadofprint 2008/01/09
pubmed 2008/01/10 09:00
medline 2008/06/05 09:00
entrez 2008/01/10 09:00
AUTHORS
NAME COLLECTIVENAME LASTNAME FORENAME INITIALS AFFILIATION AFFILIATIONINFO
Visscher PM Visscher Peter M PM Genetic Epidemiology, Queensland Institute of Medical Research, Herston, Brisbane, Australia. peter.visscher@qimr.edu.au
Andrew T Andrew Toby T
Nyholt DR Nyholt Dale R DR
INVESTIGATORS
JOURNAL
VOLUME: 16
ISSUE: 3
TITLE: European journal of human genetics : EJHG
ISOABBREVIATION: Eur. J. Hum. Genet.
YEAR: 2008
MONTH: Mar
DAY:
MEDLINEDATE:
SEASON:
CITEDMEDIUM: Print
ISSN: 1018-4813
ISSNTYPE: Print
MEDLINE JOURNAL
MEDLINETA: Eur J Hum Genet
COUNTRY: England
ISSNLINKING: 1018-4813
NLMUNIQUEID: 9302235
PUBLICATION TYPE
PUBLICATIONTYPE TEXT
Journal Article
Research Support, Non-U.S. Gov't
COMMENTS AND CORRECTIONS
GRANTS
GENERAL NOTE
KEYWORDS
MESH HEADINGS
DESCRIPTORNAME QUALIFIERNAME
Genome, Human
Humans
Quantitative Trait Loci
SUPPLEMENTARY MESH
GENE SYMBOLS
CHEMICALS
OTHER ID's