Genome-wide association studies of alcohol intake--a promising cocktail?

Integrative genomics approach identifies conserved transcriptomic networks in Alzheimer's disease

Alzheimer's disease (AD) is a devastating neurological disorder characterized by changes in cell-type proportions and consequently marked alterations of the transcriptome. Here we use a data-driven systems biology meta-analytical approach across three human AD cohorts, encompassing six cortical brain regions, and integrate with multi-scale datasets comprising of DNA methylation, histone acetylation, transcriptome- and genome-wide association studies and quantitative trait loci to further characterize the genetic architecture of AD. We perform co-expression network analysis across more than 1200 human brain samples, identifying robust AD-associated dysregulation of the transcriptome, unaltered in normal human aging. We assess the cell-type specificity of AD gene co-expression changes and estimate cell-type proportion changes in human AD by integrating co-expression modules with single-cell transcriptome data generated from 27 321 nuclei from human postmortem prefrontal cortical tissue. We also show that genetic variants of AD are enriched in a microglial AD-associated module and identify key transcription factors regulating co-expressed modules. Additionally, we validate our results in multiple published human AD gene expression datasets, which can be easily accessed using our online resource (https://swaruplab.bio.uci.edu/consensusAD).

Associations between polygenic risk for tobacco and alcohol use and liability to tobacco and alcohol use, and psychiatric disorders in an independent sample of 13,999 Australian adults

BACKGROUND

Substance use, substance use disorders (SUDs), and psychiatric disorders commonly co-occur. Genetic risk common to these complex traits is an important explanation; however, little is known about how polygenic risk for tobacco or alcohol use overlaps the genetic risk for the comorbid SUDs and psychiatric disorders.

METHODS

We constructed polygenic risk scores (PRSs) using GWAS meta-analysis summary statistics from a large discovery sample, GWAS & Sequencing Consortium of Alcohol and Nicotine use (GSCAN), for smoking initiation (SI; N = 631,564), age of initiating regular smoking (AI; N = 258,251), cigarettes per day (CPD; N = 258,999), smoking cessation (SC; N = 312,273), and drinks per week (DPW; N = 527,402). We then estimated the fixed effect of these PRSs on the liability to 15 phenotypes related to tobacco and alcohol use, substance use disorders, and psychiatric disorders in an independent target sample of Australian adults.

RESULTS

After adjusting for multiple testing, 10 of 75 combinations of discovery and target phenotypes remained significant. PRS-SI (R² range: 1.98%-5.09 %) was positively associated with SI, DPW, and with DSM-IV and FTND nicotine dependence, and conduct disorder. PRS-AI (R²: 3.91 %) negatively associated with DPW. PRS-CPD (R²: 1.56 %-1.77 %) positively associated with DSM-IV nicotine dependence and conduct disorder. PRS-DPW (R²: 3.39 %-6.26 %) positively associated with only DPW. The variation of DPW was significantly influenced by sex*PRS-SI, sex*PRS-AI and sex*PRS-DPW. Such interaction effect was not detected in the other 14 phenotypes.

CONCLUSIONS

Polygenic risks associated with tobacco use are also associated with liability to alcohol consumption, nicotine dependence, and conduct disorder.

Association between polygenic risk for tobacco or alcohol consumption and liability to licit and illicit substance use in young Australian adults

BACKGROUND

Co-morbid substance use is very common. Despite a historical focus using genetic epidemiology to investigate comorbid substance use and misuse, few studies have examined substance-substance associations using polygenic risk score (PRS) methods.

METHODS

Using summary statistics from the largest substance use GWAS to date (258,797- 632,802 subjects), GWAS and Sequencing Consortium of Alcohol and Nicotine use (GSCAN), we constructed PRSs for smoking initiation (PRS-SI), age of initiation of regular smoking (PRS-AI), cigarettes per day (PRS-CPD), smoking cessation (PRS-SC), and drinks per week (PRS-DPW). We then estimated the fixed effect of individual PRSs on 22 lifetime substance use and substance use disorder phenotypes collected in an independent sample of 2463 young Australian adults using genetic restricted maximal likelihood (GREML) in Genome-wide Complex Trait Analysis (GCTA), separately in females, males and both sexes together.

RESULTS

After accounting for multiple testing, PRS-SI significantly explained variation in the risk of cocaine (0.67%), amphetamine (1.54%), hallucinogens (0.72%), ecstasy (1.66%) and cannabis initiation (0.97%), as well as DSM-5 alcohol use disorder (0.72%). PRS-DPW explained 0.75%, 0.59% and 0.90% of the variation of cocaine, amphetamine and ecstasy initiation respectively. None of the 22 phenotypes including emergent classes of substance use were significantly predicted by PRS-AI, PRS-CPD, and PRS-SC.

CONCLUSIONS

To our knowledge, this is the first study to report significant genetic overlap between the polygenic risks for smoking initiation and alcohol consumption and the risk of initiating major classes of illicit substances. PRSs constructed from large discovery GWASs allows the detection of novel genetic associations.

Genetics of alcoholism

Multiple lines of evidence strongly indicate that genetic factors contribute to the risk for alcohol use disorders (AUD). There is substantial heterogeneity in AUD, which complicates studies seeking to identify specific genetic factors. To identify these genetic effects, several different alcohol-related phenotypes have been analyzed, including diagnosis and quantitative measures related to AUDs. Study designs have used candidate gene analyses, genetic linkage studies, genomewide association studies (GWAS), and analyses of rare variants. Two genes that encode enzymes of alcohol metabolism have the strongest effect on AUD: aldehyde dehydrogenase 2 and alcohol dehydrogenase 1B each has strongly protective variants that reduce risk, with odds ratios approximately 0.2-0.4. A number of other genes important in AUD have been identified and replicated, including GABRA2 and alcohol dehydrogenases 1B and 4. GWAS have identified additional candidates. Rare variants are likely also to play a role; studies of these are just beginning. A multifaceted approach to gene identification, targeting both rare and common variations and assembling much larger datasets for meta-analyses, is critical for identifying the key genes and pathways important in AUD.

The genetics of alcohol dependence

Alcohol consumption dates back to the Neolithic period, and alcohol dependence contributes substantially to the current global burden of disease. Despite this, optimal therapies and preventive strategies are lacking. Formal genetic studies of alcohol dependence have shown that genetic factors play as large a role in disease etiology as environmental factors. Molecular genetic studies may identify causal factors and facilitate the development of novel preventive and therapeutic approaches. Whereas earlier studies involved the use of linkage- and candidate-gene approaches, recent years have witnessed the introduction of genome-wide association studies (GWAS). The present review provides a brief overview of the findings of formal genetic studies, summarizes the results of earlier molecular-genetic investigations, and presents a detailed overview of all published GWAS in the field of alcohol dependence research. To date, few genome-wide significant findings have been reported. However, through the polygenic approach, GWAS have both confirmed the existence of a multitude of novel risk genes and indicated interesting new candidates.