Using genetic information from candidate gene and genome-wide association studies in risk prediction for alcohol dependence.
- Authors
- 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
- Year
- 2014
- Journal
- Addiction biology
- PMID
- 23362995
- DOI
- 10.1111/adb.12035
- PMCID
- PMC3664249
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 SNPs associated with AD in candidate gene studies and SNPs 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. SNPs 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 SNPs with P < 0.01 to 0.565 for SNPs with P < 0.50. This study suggests that SNPs 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.
Study overview. Gray boxes show samples used for each step of analyses. White boxes display the selection criteria for SNPs at each step.
Distribution of genetic sum scores based on candidate gene SNPs pruned at r2<0.50 in cases and controls for AD. Left panel: scores in the COGA GWAS sample independent of the COGA high-density family-based association sample. Right panel: scores in the FSCD and COGEND portion of the SAGE GWAS sample. The figure shows the frequency of normalized allele counts in bins separately for cases and controls. Allele counts were created by adding the number of risk alleles of SNPs associated with AD in candidate gene studies, and then dividing by the number of non-missing genotypes for each individual. The table summarizes the mean and range for the sum score in cases and controls.
Mean AUC estimates for varying p-value thresholds. The mean of all 100 AUC estimates for sum scores created using SNPs that meet different p-value thresholds in discovery samples is plotted here in the solid line. Dashed lines represent the upper and lower bounds of the 95% confidence interval of the mean AUC estimate.
| Name | Type |
|---|---|
| addiction | phenotype |
| ADH | gene |
| ADH1B | gene |
| ADH1B SNP local | variant |
| African American | cohort |
| African-Americans | cohort |
| alcohol | phenotype |
| alcohol dependence | phenotype |
| alcoholism | phenotype |
| alcoholism risk | phenotype |
| Alzheimer's disease | phenotype |
| autosomal SNPs | cohort |
| bipolar disorder | phenotype |
| candidate gene panel local | gene |
| Candidate gene panel local | variant |
| candidate gene SNPs local | variant |
| candidate gene sum score local | gene |
| Caucasians | cohort |
| Center for Inherited Disease Research | cohort |
| CHRM2 | gene |
| cocaine | phenotype |
| COGA family-based association sample local | cohort |
| COGA family sample local | cohort |
| COGA GWAS EA sample local | cohort |
| COGA high-density family-based association sample local | cohort |
| COGA high-density family-based sample local | cohort |
| COGA-SAGE combined sample local | cohort |
| COGA sample | cohort |
| COGEND | cohort |
| Collaborative Study on the Genetics of Alcoholism (COGA) | cohort |
| combined sample | cohort |
| complex disorders | phenotype |
| diabetes | phenotype |
| discovery samples local | cohort |
| drug dependence | phenotype |
| DSM-IV | phenotype |
| environmental factors | drug |
| European ancestry | cohort |
| expanded SNP panel local | variant |
| Family-based association results local | cohort |
| family history positive | phenotype |
| Family study of cocaine dependence | cohort |
| Feighner criteria local | phenotype |
| FSCD | cohort |
| GABRA2 | gene |
| genetic sum scores local | drug |
| genetic sum scores local | phenotype |
| genetic sum scores local | variant |
| genetic variants | cohort |
| GWAS samples local | cohort |
| HapMap CEU | cohort |
| HapMap CEU data local | cohort |
| HapMap Phase 3 CEU local | cohort |
| hundreds of variants local | variant |
| ICD-10 | phenotype |
| Illumina Human 1M DNA Analysis BeadChip local | drug |
| individual SNPs | cohort |
| marijuana | phenotype |
| nicotine | drug |
| nicotine dependence | phenotype |
| opioid | drug |
| panel of SNPs local | variant |
| population-based family studies local | cohort |
| Population-based family studies local | cohort |
| population-based sample | cohort |
| proxy SNPs | variant |
| psychiatric traits | phenotype |
| replicated variants local | variant |
| risk allele | cohort |
| rs1229984 | variant |
| SAGE | cohort |
| SAGE-COGA combined sample local | cohort |
| SAGE EA sample local | cohort |
| SAGE GWAS EA sample local | cohort |
| SAGE GWAS sample local | cohort |
| schizophrenia | phenotype |
| sedatives | drug |
| sex | phenotype |
| site | cohort |
| SNP | cohort |
| SNP panel local | variant |
| SNPs meeting p-value thresholds local | variant |
| stimulants | drug |
| Study of Addiction: Genetics and Environment | cohort |
| sum scores | drug |
| TACR3 | gene |
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