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
17785532
TITLE
Prediction of individual genetic risk to disease from genome-wide association studies.
ABSTRACT
Empirical studies suggest that the effect sizes of individual causal risk alleles underlying complex genetic diseases are small, with most genotype relative risks in the range of 1.1-2.0. Although the increased risk of disease for a carrier is small for any single locus, knowledge of multiple-risk alleles throughout the genome could allow the identification of individuals that are at high risk. In this study, we investigate the number and effect size of risk loci that underlie complex disease constrained by the disease parameters of prevalence and heritability. Then we quantify the value of prediction of genetic risk to disease using a range of realistic combinations of the number, size, and distribution of risk effects that underlie complex diseases. We propose an approach to assess the genetic risk of a disease in healthy individuals, based on dense genome-wide SNP panels. We test this approach using simulation. When the number of loci contributing to the disease is >50, a large case-control study is needed to identify a set of risk loci for use in predicting the disease risk of healthy people not included in the case-control study. For diseases controlled by 1000 loci of mean relative risk of only 1.04, a case-control study with 10,000 cases and controls can lead to selection of approximately 75 loci that explain >50% of the genetic variance. The 5% of people with the highest predicted risk are three to seven times more likely to suffer the disease than the population average, depending on heritability and disease prevalence. Whether an individual with known genetic risk develops the disease depends on known and unknown environmental factors.
DATE PUBLISHED
2007 Oct
HISTORY
PUBSTATUS PUBSTATUSDATE
aheadofprint 2007/09/04
pubmed 2007/09/06 09:00
medline 2007/12/06 09:00
entrez 2007/09/06 09:00
AUTHORS
NAME COLLECTIVENAME LASTNAME FORENAME INITIALS AFFILIATION AFFILIATIONINFO
Wray NR Wray Naomi R NR Genetic Epidemiology, Queensland Institute of Medical Research, Queensland 4029, Brisbane, Australia. Naomi.Wray@qimr.edu.au
Goddard ME Goddard Michael E ME
Visscher PM Visscher Peter M PM
INVESTIGATORS
JOURNAL
VOLUME: 17
ISSUE: 10
TITLE: Genome research
ISOABBREVIATION: Genome Res.
YEAR: 2007
MONTH: Oct
DAY:
MEDLINEDATE:
SEASON:
CITEDMEDIUM: Print
ISSN: 1088-9051
ISSNTYPE: Print
MEDLINE JOURNAL
MEDLINETA: Genome Res
COUNTRY: United States
ISSNLINKING: 1088-9051
NLMUNIQUEID: 9518021
PUBLICATION TYPE
PUBLICATIONTYPE TEXT
Journal Article
Research Support, Non-U.S. Gov't
COMMENTS AND CORRECTIONS
REFTYPE REFSOURCE REFPMID NOTE
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GRANTS
GENERAL NOTE
KEYWORDS
MESH HEADINGS
DESCRIPTORNAME QUALIFIERNAME
Algorithms
Alleles
Case-Control Studies
Genetic Diseases, Inborn genetics
Genetic Predisposition to Disease genetics
Genetics, Population genetics
Genome, Human genetics
Humans genetics
Models, Genetic genetics
Polymorphism, Single Nucleotide genetics
Risk Factors genetics
SUPPLEMENTARY MESH
GENE SYMBOLS
CHEMICALS
OTHER ID's
OTHERID SOURCE
PMC1987352 NLM
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Last Modified: Oct 15 2007