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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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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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.</description><identifier>ISSN: 1553-7404</identifier><identifier>ISSN: 1553-7390</identifier><identifier>EISSN: 1553-7404</identifier><identifier>DOI: 10.1371/journal.pgen.1002973</identifier><identifier>PMID: 23071447</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>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</subject><ispartof>PLoS genetics, 2012-10, Vol.8 (10), p.e1002973-e1002973</ispartof><rights>COPYRIGHT 2012 Public Library of Science</rights><rights>Do et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited: Do CB, Hinds DA, Francke U, Eriksson N (2012) Comparison of Family History and SNPs for Predicting Risk of Complex Disease. 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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.</description><subject>Biology</subject><subject>Cardiovascular disease</subject><subject>Coronary vessels</subject><subject>Family</subject><subject>Family medical history</subject><subject>Genetic polymorphisms</subject><subject>Genetic Predisposition to Disease</subject><subject>Genetic variation</subject><subject>Health risk assessment</subject><subject>Humans</subject><subject>Liability</subject><subject>Likelihood Functions</subject><subject>Mathematics</subject><subject>Methods</subject><subject>Models, Genetic</subject><subject>Multifactorial Inheritance</subject><subject>Pedigree</subject><subject>Polymorphism, Single Nucleotide</subject><subject>Quantitative genetics</subject><subject>Risk</subject><subject>Risk 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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.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>23071447</pmid><doi>10.1371/journal.pgen.1002973</doi><oa>free_for_read</oa></addata></record> |
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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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