Family-based association analysis of alcohol dependence criteria and severity.
- Authors
- Wetherill, Leah; Kapoor, Manav; Agrawal, Arpana; Bucholz, Kathleen; Koller, Daniel; Bertelsen, Sarah E; Le, Nhung; Wang, Jen-Chyong; Almasy, Laura; Hesselbrock, Victor; Kramer, John; Nurnberger, John I; Schuckit, Marc; Tischfield, Jay A; Xuei, Xiaoling; Porjesz, Bernice; Edenberg, Howard J; Goate, Alison M; Foroud, Tatiana
- Year
- 2014
- Journal
- Alcoholism, clinical and experimental research
- PMID
- 24015780
- DOI
- 10.1111/acer.12251
- PMCID
- PMC3946798
BACKGROUND: Despite the high heritability of alcohol dependence (AD), the genes found to be associated with it account for only a small proportion of its total variability. The goal of this study was to identify and analyze phenotypes based on homogeneous classes of individuals to increase the power to detect genetic risk factors contributing to the risk of AD. METHODS: The 7 individual DSM-IV criteria for AD were analyzed using latent class analysis (LCA) to identify classes defined by the pattern of endorsement of the criteria. A genome-wide association study was performed in 118 extended European American families (n = 2,322 individuals) densely affected with AD to identify genes associated with AD, with each of the 7 DSM-IV criteria, and with the probability of belonging to 2 of 3 latent classes. RESULTS: Heritability for DSM-IV AD was 61% and ranged from 17 to 60% for the other phenotypes. A single nucleotide polymorphism (SNP) in the olfactory receptor OR51L1 was significantly associated (7.3 × 10(-8) ) with the DSM-IV criterion of persistent desire to, or inability to, cut down on drinking. LCA revealed a 3-class model: the "low-risk" class (50%) rarely endorsed any criteria and none met criteria for AD; the "moderate-risk" class (33%) endorsed primarily 4 DSM-IV criteria and 48% met criteria for AD; and the "high-risk" class (17%) manifested high endorsement probabilities for most criteria and nearly all (99%) met criteria for AD. One SNP in a sodium leak channel NALCN demonstrated genome-wide significance with the high-risk class (p = 4.1 × 10(-8) ). Analyses in an independent sample did not replicate these associations. CONCLUSIONS: We explored the genetic contribution to several phenotypes derived from the DSM-IV AD criteria. The strongest evidence of association was with SNPs in NALCN and OR51L1.
Average probability of DSM-IV criterion endorsement within each latent classThe X-axis indicates the DSM-IV criteria. The Y-axis denotes the probability of endorsing each criterion within each latent class. The low-risk class is depicted with a dotted line. The moderate-risk class is depicted with a dashed line. The high-risk class is depicted with a solid line.
Genome-wide association study results for the phenotypes(A) alcohol dependence, (B) withdrawal, (C) gave up activities to drink, (D) time spent obtaining/using/recovering from alcohol, (E) drink despite physical/psychological problems, (F) persistent desire/inability to cut down, (G) tolerance, (H) drink more than intend to, (I) low-risk latent class probability, (J) moderate-risk latent class probability, (K) high-risk latent class probability.
Association results with key phenotypes(A) High-risk latent class probability with SNPs in the region around rs17484734 in NALCN. (B) Persistent desire/inability to cut down with SNPs in the region around rs11035201 in OR51L1. Y-axis denotes the –log10(p-value) for association. X-axis is the physical position on the chromosome (Mb). The most significantly associated SNP is shown in purple. The extent of linkage disequilibrium (as measured by r2) between each SNP and the most significantly associated SNP is indicated by the color scale at top right. Larger values of r2 indicate greater linkage disequilibrium. Genotyped SNPs are indicated as circles, and imputed SNPs by squares.
No entities extracted from this document yet.
No uploaded files.
In this knowledge base
External
| Title | Authors | Journal | Year | Link |
|---|---|---|---|---|
| Genetic risk for alcohol use disorder in relation to individual symptom criteria: Do polygenic indices provide unique information for understanding severity and heterogeneity? | Sarles YM et al. | — | 2025 | → |
| Human genetics and epigenetics of alcohol use disorder. | Zhou H et al. | — | 2024 | → |
| New insights into the physiology and pathophysiology of the atypical sodium leak channel NALCN. | Monteil A et al. | — | 2024 | → |
| Genome-wide association and replication studies for handedness in a Korean community-based cohort. | Song Y et al. | — | 2023 | → |
| Investigating genetically stratified subgroups to better understand the etiology of alcohol misuse. | Thijssen AB et al. | — | 2023 | → |
| The collaborative study on the genetics of alcoholism: Genetics. | Johnson EC et al. | — | 2023 | → |
| Sodium Leak Channel in the Nucleus Accumbens Modulates Ethanol-Induced Acute Stimulant Responses and Locomotor Sensitization in Mice: A Brief Research Report. | Wu Y et al. | — | 2021 | → |
| Recent advances in genetic studies of alcohol use disorders. | Gupta I et al. | — | 2020 | → |
| Genome-wide association studies of alcohol dependence, DSM-IV criterion count and individual criteria. | Lai D et al. | — | 2019 | → |
| Genome-wide association study identifies loci associated with liability to alcohol and drug dependence that is associated with variability in reward-related ventral striatum activity in African- and European-Americans. | Wetherill L et al. | — | 2019 | → |
| Human Genetics of Addiction: New Insights and Future Directions. | Hancock DB et al. | — | 2018 | → |
| Novel human genome variants associated with alcohol use disorders identified in a Lithuanian cohort. | Baronas K et al. | — | 2018 | → |
| Risk Locus Identification Ties Alcohol Withdrawal Symptoms to SORCS2. | Smith AH et al. | — | 2018 | → |
| Single nucleotide polymorphisms in the REG-CTNNA2 region of chromosome 2 and NEIL3 associated with impulsivity in a Native American sample. | Ehlers CL et al. | — | 2016 | → |
| Alcohol Dependence Genetics: Lessons Learned From Genome-Wide Association Studies (GWAS) and Post-GWAS Analyses. | Hart AB et al. | — | 2015 | → |
| Association of substance dependence phenotypes in the COGA sample. | Wetherill L et al. | — | 2015 | → |
| Clinically relevant genetic biomarkers from the brain in alcoholism with representation on high resolution chromosome ideograms. | Manzardo AM et al. | — | 2015 | → |
| Drosophila and Caenorhabditis elegans as Discovery Platforms for Genes Involved in Human Alcohol Use Disorder. | Grotewiel M et al. | — | 2015 | → |
| Genes associated with alcohol outcomes show enrichment of effects with broad externalizing and impulsivity phenotypes in an independent sample. | Aliev F et al. | — | 2015 | → |
| Genomic influences on alcohol problems in a population-based sample of young adults. | Edwards AC et al. | — | 2015 | → |
| The genetics of alcohol dependence: Twin and SNP-based heritability, and genome-wide association study based on AUDIT scores. | Mbarek H et al. | — | 2015 | → |
| XRCC5 as a risk gene for alcohol dependence: evidence from a genome-wide gene-set-based analysis and follow-up studies in Drosophila and humans. | Juraeva D et al. | — | 2015 | → |
| Cognitive mediators and disparities in the relation between teen depressiveness and smoking. | Mistry R et al. | — | 2014 | → |
| Genome-wide survival analysis of age at onset of alcohol dependence in extended high-risk COGA families. | Kapoor M et al. | — | 2014 | → |
| The sodium leak channel, NALCN, in health and disease. | Cochet-Bissuel M et al. | — | 2014 | → |