BackgroundRodent paradigms and human genome-wide association studies (GWASs) on drug use have the potential to provide biological insight into the pathophysiology of addiction.MethodsUsing GeneWeaver, we created rodent alcohol and nicotine gene-sets derived from 19 gene expression studies on alcohol and nicotine outcomes. We partitioned the SNP-heritability of these gene-sets using four large human GWASs: 1) alcoholic drinks per week, 2) problematic alcohol use, 3) cigarettes per day and 4) smoking cessation. We benchmarked our findings with curated human alcoholism and nicotine addiction gene-sets and performed specificity analyses using other rodent gene-sets (e.g., locomotor behavior) and other human GWASs (e.g., height).ResultsThe rodent alcohol gene-set was enriched for heritability of drinks per week, cigarettes per day, and smoking cessation, but not problematic alcohol use. However, the rodent nicotine gene-set was not significantly associated with any of these traits. Both rodent gene-sets showed enrichment for several non-substance use GWASs, and the extent of this relationship tended to increase as a function of trait heritability. In general, larger gene-sets demonstrated more significant enrichment. Finally, when evaluating human traits with similar heritabilities, both rodent gene-sets showed greater enrichment for substance use traits.ConclusionOur results suggest that rodent gene expression studies can help to identify genes that capture heritability of substance use traits in humans, yet the specificity to human substance use was less than expected due to various factors such as the genetic architecture of a trait. We outline various limitations, interpretations and considerations for future research.
ObjectivesFrom the first description by Leo Kanner [1], autism has been an enigmatic neurobehavioral phenomenon. The new genetic/genomic technologies of the past decade have not been as productive as originally anticipated in unveiling the mysteries of autism. The specific etiology of the majority of cases of autism spectrum disorder (ASD) is unknown, although numerous genetic/genomic variants and alterations of diverse cellular functions have been reported. Prompted by this failure, we have investigated whether the metabolomics approach might yield results which could simultaneously lead to a blood-based screening/diagnostic test and to treatment options. Methods Plasma samples from a clinically well-defined cohort of 100 male individuals, ages 2-16+ years, with ASD and 32 age-matched typically developing (TD) controls were subjected to global metabolomic analysis. ResultsWe have identified more than 25 plasma metabolites among the approximately 650 metabolites analyzed, representing over 70 biochemical pathways, that can discriminate children with ASD as young as 2 years from children that are developing typically. The discriminating power was greatest in the 2-10 year age group and weaker in older age groups. The initial findings were validated in a second cohort of 83 children, males and females, ages 2-10 years, with ASD and 76 age and gender-matched TD children. The discriminant metabolites were associated with several key biochemical pathways suggestive of potential contributions of increased oxidative stress, mitochondrial dysfunction, inflammation and immune dysregulation in ASD. Further, targeted quantitative analysis of a subset of discriminating metabolites using tandem mass spectrometry provided a reliable laboratory method to detect children with ASD. Conclusion Metabolic profiling appears to be a robust technique to identify children with ASD ages 2-10 years and provides insights into the altered metabolic pathways in ASD, which could lead to treatment strategies. ObjectivesTo uncover novel traits associated with nicotine and alcohol use genetics, we performed a phenome-wide association study in a large multi-ethnic cohort. Methods We investigated 7,688 African-Americans (AFR), 1,133 Asian-Americans (ASN), 14,081 European-Americans (EUR), and 3,492 Hispanic-Americans (HISP) from the Women's Health Initiative, analyzing risk alleles located in the CHRNA5-CHRNA3 locus (rs8034191, rs1051730, rs12914385, rs2036527, and rs16969968) for nicotine-related traits and ADH1B (rs1229984 and rs2066702) and ALDH2 (rs671) for alcohol-related traits with respect to anthropometric characteristics, dietary habits, social status, psychological circumstances, reproductive history, health conditions, and nicotine-and alcohol-related traits. ResultsThe investigated loci resulted associated with novel traits: rs1229984 were associated with family income (p=4.1*10 −12 ), having a pet (p=6.5*10 −11 ), partner education (p=1.8*10 −10 ), "usually expect the best" (p=2.4*10 −7), "felt calm and peaceful" (p=2.6*10 ), and num...
Animal models of drug use have been employed for over 100 years to facilitate the 10 identification of mechanisms governing human substance use and addiction. Most 11 cross-species research on drug use/addiction examines behavioral overlap, but 12 studies assessing neuro-molecular correspondence are lacking. Our study utilized 13 transcriptome-wide data from the hippocampus and ventral tegmental area 14 (VTA)/midbrain from a total of 35 human males with cocaine use disorder/controls 15 and 49 male C57BL/6J cocaine/saline administering/exposed mice. We 16hypothesized that individual genes (differential expression) and systems of co-17 expressed genes (gene networks) would demonstrate appreciable overlap across 18 mouse cocaine self-administration and human cocaine use disorder. We found 19modest, but significant associations between differentially expressed genes 20 associated with cocaine self-administration (short access) and cocaine use disorder 21 within meso-limbic circuitry, but non-robust associations with mouse models of 22 acute cocaine exposure, (cocaine) context re-exposure and cocaine + context re-23 exposure. Investigating systems of co-expressed genes, we also found several 24 validated gene networks with weak to moderate conservation between 25 cocaine/saline self-administering mice and disordered cocaine users/controls. The 26 most conserved hippocampal and VTA gene networks demonstrated substantial 27 overlap (2,029 common genes) and included novel and previously implicated 28 targets of cocaine use/addiction. Lastly, we conducted expression-based phenome-29 wide association studies of the nine common hub genes across conserved gene 30 networks and found that they were associated with dopamine/serotonin function, 31cocaine self-administration and other relevant mouse traits. Overall, our study 32 identified and characterized homologous transcriptional effects between mouse 33 models of cocaine self-administration and human cocaine use disorder that may 34 serve as a benchmark for future research. 35 36
The GeneWeaver bipartite data model provides an efficient means to evaluate shared molecular components from sets derived across diverse species, disease states and biological processes. In order to adapt this model for examining related molecular components and biological networks, such as pathway or gene network data, we have developed a means to leverage the bipartite data structure to extract and analyze shared edges. Using the Pathway Commons database we demonstrate the ability to rapidly identify shared connected components among a diverse set of pathways. In addition, we illustrate how results from maximal bipartite discovery can be decomposed into hierarchical relationships, allowing shared pathway components to be mapped through various parent-child relationships to help visualization and discovery of emergent kernel driven relationships. Interrogating common relationships among biological networks and conventional GeneWeaver gene lists will increase functional specificity and reliability of the shared biological components. This approach enables self-organization of biological processes through shared biological networks.
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