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
16933140
TITLE
Bias, precision and heritability of self-reported and clinically measured height in Australian twins.
ABSTRACT
Many studies of quantitative and disease traits in human genetics rely upon self-reported measures. Such measures are based on questionnaires or interviews and are often cheaper and more readily available than alternatives. However, the precision and potential bias cannot usually be assessed. Here we report a detailed quantitative genetic analysis of stature. We characterise the degree of measurement error by utilising a large sample of Australian twin pairs (857 MZ, 815 DZ) with both clinical and self-reported measures of height. Self-report height measurements are shown to be more variable than clinical measures. This has led to lowered estimates of heritability in many previous studies of stature. In our twin sample the heritability estimate for clinical height exceeded 90%. Repeated measures analysis shows that 2-3 times as many self-report measures are required to recover heritability estimates similar to those obtained from clinical measures. Bivariate genetic repeated measures analysis of self-report and clinical height measures showed an additive genetic correlation >0.98. We show that the accuracy of self-report height is upwardly biased in older individuals and in individuals of short stature. By comparing clinical and self-report measures we also showed that there was a genetic component to females systematically reporting their height incorrectly; this phenomenon appeared to not be present in males. The results from the measurement error analysis were subsequently used to assess the effects of error on the power to detect linkage in a genome scan. Moderate reduction in error (through the use of accurate clinical or multiple self-report measures) increased the effective sample size by 22%; elimination of measurement error led to increases in effective sample size of 41%.
DATE PUBLISHED
2006 Nov
HISTORY
PUBSTATUS PUBSTATUSDATE
received 2006/06/20
accepted 2006/08/01
aheadofprint 2006/08/25
pubmed 2006/08/26 09:00
medline 2007/05/01 09:00
entrez 2006/08/26 09:00
AUTHORS
NAME COLLECTIVENAME LASTNAME FORENAME INITIALS AFFILIATION AFFILIATIONINFO
Macgregor S Macgregor Stuart S Genetic Epidemiology, Queensland Institute of Medical Research, Herston Road, Brisbane, Australia. stuart.macgregor@qimr.edu.au
Cornes BK Cornes Belinda K BK
Martin NG Martin Nicholas G NG
Visscher PM Visscher Peter M PM
INVESTIGATORS
JOURNAL
VOLUME: 120
ISSUE: 4
TITLE: Human genetics
ISOABBREVIATION: Hum. Genet.
YEAR: 2006
MONTH: Nov
DAY:
MEDLINEDATE:
SEASON:
CITEDMEDIUM: Print
ISSN: 0340-6717
ISSNTYPE: Print
MEDLINE JOURNAL
MEDLINETA: Hum Genet
COUNTRY: Germany
ISSNLINKING: 0340-6717
NLMUNIQUEID: 7613873
PUBLICATION TYPE
PUBLICATIONTYPE TEXT
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Twin Study
COMMENTS AND CORRECTIONS
GRANTS
GRANTID AGENCY COUNTRY
AA007728 NIAAA NIH HHS United States
AA13326-01 NIAAA NIH HHS United States
AA13446-03 NIAAA NIH HHS United States
MH66206-01A1 NIMH NIH HHS United States
GENERAL NOTE
KEYWORDS
MESH HEADINGS
DESCRIPTORNAME QUALIFIERNAME
Adult
Algorithms
Analysis of Variance
Australia
Body Height genetics
Female genetics
Humans genetics
Male genetics
Middle Aged genetics
Questionnaires standards
Reproducibility of Results standards
Twins, Dizygotic genetics
Twins, Monozygotic genetics
SUPPLEMENTARY MESH
GENE SYMBOLS
CHEMICALS
OTHER ID's