Cross-species translational approaches to human genomic analyses are lacking. The present study uses an integrative framework to investigate how genes associated with nicotine use in model organisms contribute to the genetic architecture of human tobacco consumption. First, we created a model organism geneset by collecting results from five animal models of nicotine exposure (RNA expression changes in brain) and then tested the relevance of these genes and flanking genetic variation using genetic data from human cigarettes per day (UK BioBank N = 123,844; all European Ancestry). We tested three hypotheses: (1) DNA variation in, or around, the ‘model organism geneset’ will contribute to the heritability to human tobacco consumption, (2) that the model organism genes will be enriched for genes associated with human tobacco consumption, and (3) that a polygenic score based off our model organism geneset will predict tobacco consumption in the AddHealth sample (N = 1667; all European Ancestry). Our results suggested that: (1) model organism genes accounted for ~5–36% of the observed SNP-heritability in human tobacco consumption (enrichment: 1.60–31.45), (2) model organism genes, but not negative control genes, were enriched for the gene-based associations (MAGMA, H-MAGMA, SMultiXcan) for human cigarettes per day, and (3) polygenic scores based on our model organism geneset predicted cigarettes per day in an independent sample. Altogether, these findings highlight the advantages of using multiple species evidence to isolate genetic factors to better understand the etiological complexity of tobacco and other nicotine consumption.
Chronic cigarette smoking is associated with increased risk for myriad health consequences including cognitive decline and dementia, but research on the link between smoking and brain structure is nascent. We assessed the relationship of cigarette smoking (ever smoked, cigarettes per day, and duration) with gray and white matter using the UK Biobank cohort (gray matter N = 19,615; white matter N = 17,760), adjusting for numerous demographic and health confounders. Ever smoked and duration were associated with smaller total gray matter volume. Ever smoked was associated with reduced volume of the right VIIIa cerebellum, as well as elevated white matter hyperintensity volumes. Smoking duration was associated with reduced total white matter volume. With regard to specific tracts, ever smoked was associated with reduced fractional anisotropy in the left cingulate gyrus part of the cingulum, left posterior thalamic radiation, and bilateral superior thalamic radiation and increased mean diffusivity in the middle cerebellar peduncle, right medial lemniscus, bilateral posterior thalamic radiation, and bilateral superior thalamic radiation. Overall, we found significant associations of cigarette exposure with global measures of gray and white matter. Furthermore, we found select associations of ever smoked, but not cigarettes per day or duration, with specific gray and white matter regions. These findings inform our understanding of the connections between smoking and variation in brain structure and clarify potential mechanisms of risk for common neurological sequelae.
The National Institute on Drug Abuse Genetics and Epigenetics Cross‐Cutting Research Team convened a diverse group of researchers, clinicians, and healthcare providers on the campus of the University of California, San Diego, in June 2018. The goal was to develop strategies to integrate genetics and phenotypes across species to achieve a better understanding of substance use disorders through associations between genotypes and addictive behaviors. This conference (a) discussed progress in harmonizing large opioid genetics cohorts, (b) discussed phenotypes that are used for genetics studies in humans, (c) examined phenotypes that are used for genetics studies in animal models, (d) identified synergies and gaps in phenotypic analyses of human and animal models and (e) identified strategies to integrate genetics and genomics data with phenotypes across species. The meeting consisted of panels that focused on phenotype harmonization (Dr. Laura Bierut, Dr. Olivier George, Dr. Dan Larach and Dr. Sesh Mudumbai), translating genetic findings between species (Dr. Elissa Chesler, Dr. Gary Peltz and Dr. Abraham Palmer), interpreting and understanding allelic variations (Dr. Vanessa Troiani and Dr. Tamara Richards) and pathway conservation in animal models and human studies (Dr. Robert Hitzemann, Dr. Huda Akil and Dr. Laura Saba). There were also updates that were provided by large consortia (Dr. Susan Tapert, Dr. Danielle Dick, Dr. Howard Edenberg and Dr. Eric Johnson). Collectively, the conference was convened to discuss progress and changes in genome‐wide association studies.
Genetic mechanisms of alternative mRNA splicing have been shown in the brain for a variety of neuropsychiatric traits, but not substance use disorders. Our study utilized RNA-sequencing data on alcohol use disorder (AUD) in four brain regions (n = 56; ages 40–73; 100% ‘Caucasian’; PFC, NAc, BLA and CEA) and genome-wide association data on AUD (n = 435,563, ages 22–90; 100% European-American). Polygenic scores of AUD were associated with AUD-related alternative mRNA splicing in the brain. We identified 714 differentially spliced genes between AUD vs controls, which included both putative addiction genes and novel gene targets. We found 6463 splicing quantitative trait loci (sQTLs) that linked to the AUD differentially spliced genes. sQTLs were enriched in loose chromatin genomic regions and downstream gene targets. Additionally, the heritability of AUD was enriched for DNA variants in and around differentially spliced genes associated with AUD. Our study also performed splicing transcriptome-wide association studies (TWASs) of AUD and other drug use traits that unveiled specific genes for follow-up and splicing correlations across SUDs. Finally, we showed that differentially spliced genes between AUD vs control were also associated with primate models of chronic alcohol consumption in similar brain regions. Our study found substantial genetic contributions of alternative mRNA splicing in AUD.
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