The collaborative study on the genetics of alcoholism: Genetics

The collaborative study on the genetics of alcoholism: Genetics

In the 4th edition of the DSM (DSM-IV), alcohol dependence (AD) and abuse were considered as mutually exclusive diagnoses that together made up AUDs. DSM-V14, 15 on the other hand consolidated AD and abuse as a single disorder as AUD15,16. By considering AD and abuse under single umbrella increased the number of diagnosed subjects, but this number was still not large enough to design powerful GWAS studies. Therefore, many genetic studies of alcoholism also concentrated on nonclinical phenotypes, such as alcohol consumption and Alcohol Use Disorders Identification Test (AUDIT)17–19, from large population based cohorts. The AUDIT, a 10-item, self-reported test was developed by the World Health Organization genetics of alcoholism as a screen for hazardous and harmful drinking and can be used as a total (AUDIT-T), AUDIT-Consumption (AUDIT-C) and AUDIT-Problems (AUDIT-P) sub-scores. Alcohol is widely consumed; however, excessive use creates serious physical, psychological and social problems and contributes to the pathogenesis of many diseases.

Pleiotropy and genetically inferred causality linking multisite chronic pain to substance use disorders

Postulating a 28-percent prevalence rate for alcohol problems in the general population, the risk of alcoholism in adopted-away sons from alcoholic backgrounds is significantly greater than that for the general population. By using archival records, the Stockholm study was able to obtain data on the entire sample of adoptees. Thus, prevalence rates for alcoholism are available for the total sample of biological parents and adoptees.

National Institute on Alcohol Abuse and Alcoholism (NIAAA)

Taken together, these waves of longitudinal follow‐up provide a perspective of AUD risk and resilience across the lifespan. Studies on mice have identified more than 80 genes that affect alcohol preference drinking 59. Pioneering work by Buck and colleagues identified three genomic regions on mouse chromosomes 1, 4 and 11 that influence acute alcohol withdrawal 71. Through a succession of studies involving F2 intercrosses, construction of recombinant inbred lines, and interval-specific congenic strains 71–73, the gene encoding multiple PDZ domain protein (Mpdz) was identified as a quantitative trait gene for alcohol withdrawal symptoms.

• It seems implausible, however, that this effect could completely explain the elevated risk to adopted-away sons of alcoholic parents, since their risk is no less than that to nonadopted sons of alcoholics.
• Alcohol use disorder, and other substance use disorders are often misunderstood and stigmatized.
• The number of unaffected sibling pairs genotyped in the replication sample was too small to analyze.
• This difference between the U.S. and Scandinavian data appears to be explained largely by differences in Scandinavian males, with estimates for Scandinavian women being close to those for U.S. men and women.
• Approximately 75% of the families were ascertained via a proband in treatment for alcohol dependence.

Genome-wide association analyses

In this study, we use the same definitions, defining AUD by meta-analyzing AUD and AD across all datasets, and defining PAU by meta-analyzing AUD, AD and AUDIT–P (Table 1). Independent genetic signals from the cross-ancestry meta-analysis were searched in OpenTargets.org37 for druggability and medication target status based on their nearest genes. Among them, OPRM1 implicated naltrexone and GABRA4 may implicate acamprosate, both current treatments for AUD. Additionally, DRD2, CACNA1C, DPYD, PDE4B, KLB, BRD3, NCAM1, FTO and MAPT were identified as druggable genes. To compare within- and cross-ancestry fine mapping, we performed within-ancestry fine mapping for the above 92 regions using the same SNP sets and EUR-only LD information (Fig. 2b,c). The median number of SNPs in the credible sets was 13, with 7 credible sets containing a single variant and 26 containing ≤5 variants, indicating that cross-ancestry fine mapping improved causal variant identification, consistent with other studies reporting improved fine mapping by including other ancestries12.

Significant associations are found between Temperance Board registrations for biological fathers and their adopted-away sons (i.e., a risk ratio of 1.3) and for biological mothers and their adopted-away daughters (i.e., a risk ratio of 2.9). However, the risk ratios for opposite-sex pair comparisons (i.e., mother-son and father-daughter pairs), although greater than one, are not statistically significant. According to the findings, 8.9 percent of the fathers and 1.6 percent of the mothers who gave their offspring up for adoption had been hospitalized for alcoholism. Heath and colleagues (in press) estimated that the proportion of all adults in the population of Copenhagen who were in the same age range as the biological parents and who had been hospitalized for alcoholism at some stage in their lives was 2 percent for men and 0.5 percent for women. Compared with what would be expected for the population as a whole, the lifetime prevalence of hospitalization for alcoholism is at least four times higher in the biological fathers and three times higher in the biological mothers of the children who were given up for adoption. Therefore, if alcoholism is genetically influenced, then adoptees as a group would be at higher risk than the general population and would have elevated rates of alcoholism.

Supplementary Data 35

Among all SNPs that were significant at a nominal P-value in the studies described above, the gene encoding cadherin 13 (CDH13) was replicated in four independent studies, and eight genes were common across any three studies (Table 1). In addition, five differentially expressed genes in different areas of postmortem human brains of alcoholics were replicated in any of three transcriptional profiling studies (Table 1) 36–41. The two earliest Iowa adoption studies (i.e., the LSS and CFS) show significantly elevated risk to adopted-away sons from alcoholic biological backgrounds compared with control adoptees (i.e., risk ratios of 3.5 and 3.6, respectively), consistent with a genetic influence on alcoholism risk in men. For male adoptees in the remaining two samples, the risk to those from an alcoholic background is not significantly higher than that for control adoptees. In these latter studies, however, the rates of alcoholism are high, even https://ecosoberhouse.com/article/kudzu-extract-and-alcohol-addiction-can-it-help-you-drink-less/ in the control adoptees (from 55 to 58 percent), raising the possibility that the entire sample of adoptees, on average, came from high-risk biological backgrounds.

Supplementary Data 12

This overview provides the framework for the development of COGA as a scientific resource in the past three decades, with individual reviews providing in‐depth descriptions of data on and discoveries from behavioral and clinical, brain function, genetic and functional genomics data. The value of COGA also resides in its data sharing policies, its efforts to communicate scientific findings to the broader community via a project website and its potential to nurture early career investigators and to generate independent research that has broadened the impact of gene‐brain‐behavior research into AUD. The Collaborative Study on the Genetics of Alcoholism (COGA) is a large-scale family study designed to identify genes that affect the risk for alcoholism (i.e., alcohol dependence) and alcohol-related characteristics and behaviors (i.e., phenotypes1).

Within- and cross-ancestry causal variant fine mapping

H.Z., R.L.K., J.D.D., H.X., S.T., K.Y., P.A.L., L.F., L.W., A.S.H., J.J., H.L., T.T.M., J.X., K.J.A.J., E.C.J. and T.T.N. performed the analyses. And P.A.L. J.G., H.R.K., M.B.S., A.C.J., A.D.B., D.D., N.G.M., S.E.M., A.C.H., P.A.F.M., P.A.L., H.J.E., A.A. And J.W.S. provided critical support regarding phenotypes and data in individual datasets. We performed gene-based association analysis for PAU or AUD in multiple ancestries using MAGMA implemented in FUMA78. Bonferroni corrections for the number of genes tested (range from 18,390 to 19,002 in different ancestries) were used to determine GWS genes.

• Estimates of risk ratios for relatives of alcoholics, which express risk to relatives as a ratio of the risk in the general population, are similarly variable.
• Individual reviews in this issue provide detailed illustrations of the ways in which COGA data have contributed towards advancing our understanding of the etiology, course and consequences of AUD, and pathways from onset to remission and relapse.
• For male adoptees in the remaining two samples, the risk to those from an alcoholic background is not significantly higher than that for control adoptees.
• Data from the LSS and CFS studies also allow us to examine the association between alcohol problems in the adoptive family and the occurrence of alcoholism in the adoptee.

Although we found no significant difference in PRS between males and females, because of the substantially smaller number of women in MVP, there is much less power for the PRS in this subgroup and for comparing the PRS by sex. The most significant pathway is reactome ethanol oxidation for both traits in both EAs and AAs. Multiple GO biological processes are enriched for AUDIT-C (Supplementary Data 13, Supplementary Fig. 17) and AUD (Supplementary Data 14, Supplementary Fig. 18), including ethanol and alcohol metabolism. Enrichments for chemical and genetic perturbation gene sets and for the GWAS catalog for both traits are shown in Supplementary Data 15–18 and Supplementary Figs. “This is a global effort to unravel complex diseases at the single-cell level, which will lead to a better understanding of the molecular and cellular perturbations in individuals with Alzheimer’s disease, alcohol use disorder, and their interactions.”

• Alcohol use disorder (AUD) is a diagnosis once referred to as “alcoholism.” It’s a condition characterized by patterns of excessive alcohol misuse despite negative consequences and major distress in important areas of daily function.
• Such selective placement would cause the importance of genetic effects to be overestimated.
• This article does not contain any studies with human or animal subjects performed by any of the authors.
• It was supported by the National Institute on Drug Abuse (NIDA), the National Institute on Alcohol Abuse and Alcoholism (NIAAA), the National Institute of Mental Health (NIMH), the Eunice Kennedy Shriver National Institute of Child Health and Human Development, and the National Institute on Aging.
• A key finding from recent studies is that both AUD and AUDIT–P differ phenotypically and genetically from typical alcohol consumption7,10,13.
• A PheWAS using logistic regression models with either AUDIT-C or AUD PRS as the independent variable, phecodes as the dependent variables, and age, sex and the first five PCs as covariates were used to identify secondary phenotypic associations.

With current review, we aim to present the recent advances in genetic and molecular studies of AUDs. Recent successes in genetic studies of AUDs will definetely motivate researchers and lead to better therapeutic interventions for this complex disorder. Participants with at least one inpatient or two outpatient ICD-9/10 codes for AUD were assigned as AUD cases, while participants with zero ICD codes for AUD were controls. In total, 80,028, 36,330, 10,150, 701 and 107 cases were included in EUR, AFR, LA, EAS and SAS, respectively, and 368,113, 79,100, 28,812, 6,254 and 389 controls were included in EUR, AFR, LA, EAS and SAS, respectively. BOLT-LMM65 was used to correct for relatedness, with age, sex and the first ten PCs as covariates. B, Ninety-two regions in a cross-ancestry analysis were fine mapped and a direct comparison was done for these regions in EUR.