Comparison of family history and SNPs for predicting risk of complex disease

The clinical utility of family history and genetic tests is generally well understood for simple Mendelian disorders and rare subforms of complex diseases that are directly attributable to highly penetrant genetic variants. However, little is presently known regarding the performance of these method...

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Veröffentlicht in:PLoS genetics 2012-10, Vol.8 (10), p.e1002973-e1002973
Hauptverfasser: Do, Chuong B, Hinds, David A, Francke, Uta, Eriksson, Nicholas
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creator Do, Chuong B
Hinds, David A
Francke, Uta
Eriksson, Nicholas
description The clinical utility of family history and genetic tests is generally well understood for simple Mendelian disorders and rare subforms of complex diseases that are directly attributable to highly penetrant genetic variants. However, little is presently known regarding the performance of these methods in situations where disease susceptibility depends on the cumulative contribution of multiple genetic factors of moderate or low penetrance. Using quantitative genetic theory, we develop a model for studying the predictive ability of family history and single nucleotide polymorphism (SNP)-based methods for assessing risk of polygenic disorders. We show that family history is most useful for highly common, heritable conditions (e.g., coronary artery disease), where it explains roughly 20%-30% of disease heritability, on par with the most successful SNP models based on associations discovered to date. In contrast, we find that for diseases of moderate or low frequency (e.g., Crohn disease) family history accounts for less than 4% of disease heritability, substantially lagging behind SNPs in almost all cases. These results indicate that, for a broad range of diseases, already identified SNP associations may be better predictors of risk than their family history-based counterparts, despite the large fraction of missing heritability that remains to be explained. Our model illustrates the difficulty of using either family history or SNPs for standalone disease prediction. On the other hand, we show that, unlike family history, SNP-based tests can reveal extreme likelihood ratios for a relatively large percentage of individuals, thus providing potentially valuable adjunctive evidence in a differential diagnosis.
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subjects Biology
Cardiovascular disease
Coronary vessels
Family
Family medical history
Genetic polymorphisms
Genetic Predisposition to Disease
Genetic variation
Health risk assessment
Humans
Liability
Likelihood Functions
Mathematics
Methods
Models, Genetic
Multifactorial Inheritance
Pedigree
Polymorphism, Single Nucleotide
Quantitative genetics
Risk
Risk assessment
Risk factors
ROC Curve
Stock options
title Comparison of family history and SNPs for predicting risk of complex disease
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