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Using genetic information from candidate gene and genome‐wide association studies in risk prediction for alcohol dependence
Author(s) -
Yan Jia,
Aliev Fazil,
Webb Bradley T.,
Kendler Kenneth S.,
Williamson Vernell S.,
Edenberg Howard J.,
Agrawal Arpana,
Kos Mark Z.,
Almasy Laura,
Nurnberger John I.,
Schuckit Marc A.,
Kramer John R.,
Rice John P.,
Kuperman Samuel,
Goate Alison M.,
Tischfield Jay A.,
Porjesz Bernice,
Dick Danielle M.
Publication year - 2014
Publication title -
addiction biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.445
H-Index - 78
eISSN - 1369-1600
pISSN - 1355-6215
DOI - 10.1111/adb.12035
Subject(s) - genome wide association study , genetic association , candidate gene , association (psychology) , alcohol dependence , computational biology , genetics , alcohol , gene , biology , psychology , single nucleotide polymorphism , genotype , biochemistry , psychotherapist
Family‐based and genome‐wide association studies ( GWAS ) of alcohol dependence ( AD ) have reported numerous associated variants. The clinical validity of these variants for predicting AD compared with family history information has not been reported. Using the Collaborative Study on the Genetics of Alcoholism ( COGA ) and the Study of Addiction: Genes and Environment ( SAGE ) GWAS samples, we examined the aggregate impact of multiple single nucleotide polymorphisms ( SNPs ) on risk prediction. We created genetic sum scores by adding risk alleles associated in discovery samples, and then tested the scores for their ability to discriminate between cases and controls in validation samples. Genetic sum scores were assessed separately for SNP s associated with AD in candidate gene studies and SNP s from GWAS analyses that met varying P ‐value thresholds. Candidate gene sum scores did not exhibit significant predictive accuracy. Family history was a better classifier of case‐control status, with a significant area under the receiver operating characteristic curve ( AUC ) of 0.686 in COGA and 0.614 in SAGE . SNP s that met less stringent P ‐value thresholds of 0.01–0.50 in GWAS analyses yielded significant AUC estimates, ranging from mean estimates of 0.549 for SNP s with P < 0.01 to 0.565 for SNP s with P < 0.50. This study suggests that SNP s currently have limited clinical utility, but there is potential for enhanced predictive ability with better understanding of the large number of variants that might contribute to risk.