Browsing by Author "Chao, Michael"

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    Analysis of whole genome-transcriptomic organization in brain to identify genes associated with alcoholism
    (Springer Nature, 2019-02-14) Kapoor, Manav; Wang, Jen-Chyong; Farris, Sean P.; Liu, Yunlong; McClintick, Jeanette; Gupta, Ishaan; Meyers, Jacquelyn L.; Bertelsen, Sarah; Chao, Michael; Nurnberger, John; Tischfield, Jay; Harari, Oscar; Zeran, Li; Hesselbrock, Victor; Bauer, Lance; Raj, Towfique; Porjesz, Bernice; Agrawal, Arpana; Foroud, Tatiana; Edenberg, Howard J.; Mayfield, R. Dayne; Goate, Alison; Medical and Molecular Genetics, School of Medicine
    Alcohol exposure triggers changes in gene expression and biological pathways in human brain. We explored alterations in gene expression in the Pre-Frontal Cortex (PFC) of 65 alcoholics and 73 controls of European descent, and identified 129 genes that showed altered expression (FDR < 0.05) in subjects with alcohol dependence. Differentially expressed genes were enriched for pathways related to interferon signaling and Growth Arrest and DNA Damage-inducible 45 (GADD45) signaling. A coexpression module (thistle2) identified by weighted gene co-expression network analysis (WGCNA) was significantly correlated with alcohol dependence, alcohol consumption, and AUDIT scores. Genes in the thistle2 module were enriched with genes related to calcium signaling pathways and showed significant downregulation of these pathways, as well as enrichment for biological processes related to nicotine response and opioid signaling. A second module (brown4) showed significant upregulation of pathways related to immune signaling. Expression quantitative trait loci (eQTLs) for genes in the brown4 module were also enriched for genetic associations with alcohol dependence and alcohol consumption in large genome-wide studies included in the Psychiatric Genetic Consortium and the UK Biobank's alcohol consumption dataset. By leveraging multi-omics data, this transcriptome analysis has identified genes and biological pathways that could provide insight for identifying therapeutic targets for alcohol dependence.
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    Association of Polygenic Liability for Alcohol Dependence and EEG Connectivity in Adolescence and Young Adulthood
    (MDPI, 2019-10-17) Meyers, Jacquelyn L.; Chorlian, David B.; Johnson, Emma C.; Pandey, Ashwini K.; Kamarajan, Chella; Salvatore, Jessica E.; Aliev, Fazil; Subbie-Saenz de Viteri, Stacey; Zhang, Jian; Chao, Michael; Kapoor, Manav; Hesselbrock, Victor; Kramer, John; Kuperman, Samuel; Nurnberger, John; Tischfield, Jay; Goate, Alison; Foroud, Tatiana; Dick, Danielle M.; Edenberg, Howard J.; Agrawal, Arpana; Porjesz, Bernice; Medical and Molecular Genetics, School of Medicine
    Differences in the connectivity of large-scale functional brain networks among individuals with alcohol use disorders (AUD), as well as those at risk for AUD, point to dysfunctional neural communication and related cognitive impairments. In this study, we examined how polygenic risk scores (PRS), derived from a recent GWAS of DSM-IV Alcohol Dependence (AD) conducted by the Psychiatric Genomics Consortium, relate to longitudinal measures of interhemispheric and intrahemispheric EEG connectivity (alpha, theta, and beta frequencies) in adolescent and young adult offspring from the Collaborative Study on the Genetics of Alcoholism (COGA) assessed between ages 12 and 31. Our findings indicate that AD PRS (p-threshold < 0.001) was associated with increased fronto-central, tempo-parietal, centro-parietal, and parietal-occipital interhemispheric theta and alpha connectivity in males only from ages 18-31 (beta coefficients ranged from 0.02-0.06, p-values ranged from 10-6-10-12), but not in females. Individuals with higher AD PRS also demonstrated more performance deficits on neuropsychological tasks (Tower of London task, visual span test) as well as increased risk for lifetime DSM-5 alcohol and opioid use disorders. We conclude that measures of neural connectivity, together with neurocognitive performance and substance use behavior, can be used to further understanding of how genetic risk variants from large GWAS of AUD may influence brain function. In addition, these data indicate the importance of examining sex and developmental effects, which otherwise may be masked. Understanding of neural mechanisms linking genetic variants emerging from GWAS to risk for AUD throughout development may help to identify specific points when neurocognitive prevention and intervention efforts may be most effective.
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    Genome-wide admixture mapping of DSM-IV alcohol dependence, criterion count, and the self-rating of the effects of ethanol in African American populations
    (Wiley, 2021-04) Lai, Dongbing; Kapoor, Manav; Wetherill, Leah; Schwandt, Melanie; Ramchandani, Vijay A.; Goldman, David; Chao, Michael; Almasy, Laura; Bucholz, Kathleen; Hart, Ronald P.; Kamarajan, Chella; Meyers, Jacquelyn L.; Nurnberger, John I., Jr.; Tischfield, Jay; Edenberg, Howard J.; Schuckit, Marc; Goate, Alison; Scott, Denise M.; Porjesz, Bernice; Agrawal, Arpana; Foroud, Tatiana; Medical and Molecular Genetics, School of Medicine
    African Americans (AA) have lower prevalence of alcohol dependence and higher subjective response to alcohol than European Americans. Genome-wide association studies (GWAS) have identified genes/variants associated with alcohol dependence specifically in AA; however, the sample sizes are still not large enough to detect variants with small effects. Admixture mapping is an alternative way to identify alcohol dependence genes/variants that may be unique to AA. In this study, we performed the first admixture mapping of DSM-IV alcohol dependence diagnosis, DSM-IV alcohol dependence criterion count, and two scores from the self-rating of effects of ethanol (SRE) as measures of response to alcohol: the first five times of using alcohol (SRE-5) and average of SRE across three times (SRE-T). Findings revealed a region on chromosome 4 that was genome-wide significant for SRE-5 (p value = 4.18E-05). Fine mapping did not identify a single causal variant to be associated with SRE-5; instead, conditional analysis concluded that multiple variants collectively explained the admixture mapping signal. PPARGC1A, a gene that has been linked to alcohol consumption in previous studies, is located in this region. Our finding suggests that admixture mapping is a useful tool to identify genes/variants that may have been missed by current GWAS approaches in admixed populations.