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Browsing by Author "Thorgeirsson, Thorgeir"
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Item Integration of evidence across human and model organism studies: A meeting report(Wiley, 2021-04-23) Palmer, Rohan H.C.; Johnson, Emma C.; Won, Hyejung; Polimanti, Renato; Kapoor, Manav; Chitre, Apurva; Bogue, Molly A.; Benca-Bachman, Chelsie E.; Parker, Clarissa C.; Verm, Anurag; Reynolds, Timothy; Ernst, Jason; Bray, Michael; Kwon, Soo Bin; Lai, Dongbing; Quach, Bryan C.; Gaddis, Nathan C.; Saba, Laura; Chen, Hao; Hawrylycz, Michael; Zhang, Shan; Zhou, Yuan; Mahaffey, Spencer; Fischer, Christian; Sanchez-Roige, Sandra; Bandrowski, Anita; Lu, Qing; Shen, Li; Philip, Vivek; Gelernter, Joel; Bierut, Laura J.; Hancock, Dana B.; Edenberg, Howard J.; Johnson, Eric O.; Nestler, Eric J.; Barr, Peter B.; Prins, Pjotr; Smith, Desmond J.; Akbarian, Schahram; Thorgeirsson, Thorgeir; Walton, Dave; Baker, Erich; Jacobson, Daniel; Palmer, Abraham A.; Miles, Michael; Chesler, Elissa J.; Emerson, Jake; Agrawal, Arpana; Martone, Maryann; Williams, Robert W.; Medical and Molecular Genetics, School of MedicineThe National Institute on Drug Abuse and Joint Institute for Biological Sciences at the Oak Ridge National Laboratory hosted a meeting attended by a diverse group of scientists with expertise in substance use disorders (SUDs), computational biology, and FAIR (Findability, Accessibility, Interoperability, and Reusability) data sharing. The meeting's objective was to discuss and evaluate better strategies to integrate genetic, epigenetic, and 'omics data across human and model organisms to achieve deeper mechanistic insight into SUDs. Specific topics were to (a) evaluate the current state of substance use genetics and genomics research and fundamental gaps, (b) identify opportunities and challenges of integration and sharing across species and data types, (c) identify current tools and resources for integration of genetic, epigenetic, and phenotypic data, (d) discuss steps and impediment related to data integration, and (e) outline future steps to support more effective collaboration-particularly between animal model research communities and human genetics and clinical research teams. This review summarizes key facets of this catalytic discussion with a focus on new opportunities and gaps in resources and knowledge on SUDs.Item Multi-ancestral genome-wide association study of clinically defined nicotine dependence reveals strong genetic correlations with other substance use disorders and health-related traits(medRxiv, 2025-02-03) Johnson, Emma C.; Lai, Dongbing; Miller, Alex P.; Hatoum, Alexander S.; Deak, Joseph D.; Balbona, Jared V.; Baranger, David A. A.; Galimberti, Marco; Sanichwankul, Kittipong; Thorgeirsson, Thorgeir; McColbert, Sarah; Sanchez-Roige, Sandra; Adhikari, Keyrun; Docherty, Anna; Degenhardt, Louisa; Edwards, Tobias; Fox, Louis; Giannelis, Alexandros; Jeffries, Paul; Korhonen, Tellervo; Morrison, Claire; Nunez, Yaira Z.; Palviainen, Teemu; Su, Mei-Hsin; Romero Villela, Pamela N.; Wetherill, Leah; Willoughby, Emily A.; Zellers, Stephanie; Bierut, Laura; Buchwald, Jadwiga; Copeland, William; Corley, Robin; Friedman, Naomi P.; Foroud, Tatiana M.; Gillespie, Nathan A.; Gizer, Ian R.; Heath, Andrew C.; Hickie, Ian B.; Kaprio, Jaakko A.; Keller, Matthew C.; Lee, James L.; Lind, Penelope A.; Madden, Pamela A.; Maes, Hermine H. M.; Martin, Nicholas G.; McGue, Matt; Medland, Sarah E.; Nelson, Elliot C.; Pearson, John V.; Porjesz, Bernice; Stallings, Michael; Vrieze, Scott; Wilhelmsen, Kirk C.; Walters, Raymond K.; Polimanti, Renato; Malison, Robert T.; Zhou, Hang; Stefansson, Kari; Potenza, Marc N.; Mutirangura, Apiwat; Shotelersuk, Vorasuk; Kalayasiri, Rasmon; Edenberg, Howard J.; Gelernter, Joel; Agrawal, Arpana; Medical and Molecular Genetics, School of MedicineGenetic research on nicotine dependence has utilized multiple assessments that are in weak agreement. We conducted a genome-wide association study of nicotine dependence defined using the Diagnostic and Statistical Manual of Mental Disorders (DSM-NicDep) in 61,861 individuals (47,884 of European ancestry, 10,231 of African ancestry, 3,746 of East Asian ancestry) and compared the results to other nicotine-related phenotypes. We replicated the well-known association at the CHRNA5 locus (lead SNP: rs147144681, p =1.27E-11 in European ancestry; lead SNP = rs2036527, p = 6.49e-13 in cross-ancestry analysis). DSM-NicDep showed strong positive genetic correlations with cannabis use disorder, opioid use disorder, problematic alcohol use, lung cancer, material deprivation, and several psychiatric disorders, and negative correlations with respiratory function and educational attainment. A polygenic score of DSM-NicDep predicted DSM-5 tobacco use disorder and 6 of 11 individual diagnostic criteria, but none of the Fagerström Test for Nicotine Dependence (FTND) items, in the independent NESARC-III sample. In genomic structural equation models, DSM-NicDep loaded more strongly on a previously identified factor of general addiction liability than did a "problematic tobacco use" factor (a combination of cigarettes per day and nicotine dependence defined by the FTND). Finally, DSM-NicDep was strongly genetically correlated with a GWAS of tobacco use disorder as defined in electronic health records, suggesting that combining the wide availability of diagnostic EHR data with nuanced criterion-level analyses of DSM tobacco use disorder may produce new insights into the genetics of this disorder.Item Multi-trait genome-wide association study of opioid addiction: OPRM1 and beyond(Springer Nature, 2022-10-07) Gaddis, Nathan; Mathur, Ravi; Marks, Jesse; Zhou, Linran; Quach, Bryan; Waldrop, Alex; Levran, Orna; Agrawal, Arpana; Randesi, Matthew; Adelson, Miriam; Jeffries, Paul W.; Martin, Nicholas G.; Degenhardt, Louisa; Montgomery, Grant W.; Wetherill, Leah; Lai, Dongbing; Bucholz, Kathleen; Foroud, Tatiana; Porjesz, Bernice; Runarsdottir, Valgerdur; Tyrfingsson, Thorarinn; Einarsson, Gudmundur; Gudbjartsson, Daniel F.; Webb, Bradley Todd; Crist, Richard C.; Kranzler, Henry R.; Sherva, Richard; Zhou, Hang; Hulse, Gary; Wildenauer, Dieter; Kelty, Erin; Attia, John; Holliday, Elizabeth G.; McEvoy, Mark; Scott, Rodney J.; Schwab, Sibylle G.; Maher, Brion S.; Gruza, Richard; Kreek, Mary Jeanne; Nelson, Elliot C.; Thorgeirsson, Thorgeir; Stefansson, Kari; Berrettini, Wade H.; Gelernter, Joel; Edenberg, Howard J.; Bierut, Laura; Hancock, Dana B.; Johnson, Eric Otto; Medical and Molecular Genetics, School of MedicineOpioid addiction (OA) is moderately heritable, yet only rs1799971, the A118G variant in OPRM1, has been identified as a genome-wide significant association with OA and independently replicated. We applied genomic structural equation modeling to conduct a GWAS of the new Genetics of Opioid Addiction Consortium (GENOA) data together with published studies (Psychiatric Genomics Consortium, Million Veteran Program, and Partners Health), comprising 23,367 cases and effective sample size of 88,114 individuals of European ancestry. Genetic correlations among the various OA phenotypes were uniformly high (rg > 0.9). We observed the strongest evidence to date for OPRM1: lead SNP rs9478500 (p = 2.56 × 10-9). Gene-based analyses identified novel genome-wide significant associations with PPP6C and FURIN. Variants within these loci appear to be pleiotropic for addiction and related traits.Item Whole Genome Sequencing of Pedigrees With High Density of Substance Use and Psychiatric Disorders: A Meeting Report(Wiley, 2025) Hill, Shirley Y.; Edenberg, Howard J.; Corvin, Aiden; Thorgeirsson, Thorgeir; Below, Jennifer E.; Goldman, David; Leal, Suzanne; Almasy, Laura; Cox, Nancy J.; Daly, Mark; Neale, Benjamin; Vrieze, Scott; Zoghbi, Huda; Biochemistry and Molecular Biology, School of MedicineThe National Institute of Drug Abuse convened a panel of scientists with expertise in substance use disorders (SUD) and genetic methodologies primarily to determine the feasibility of performing whole genome sequencing utilizing existing pedigree collections with a high density of SUD and psychiatric disorders. A major focus was on determining if there had been any successes in identifying genetic variants for complex traits in family-based designs. Such information could provide assurance that whole genome sequencing might provide significant pay-offs particularly in the pursuit of rare variants and copy number variants. An important goal was to discuss and evaluate optimal strategies for studying genetic variants in human samples. Specific topics were (a) to consider whether a smaller number of cases typically available in family studies versus the larger number available in biobanks can reveal unique information; (b) to identify potential gaps in information available in biobank data that might be supplemented with family data; (c) to consider the optimal SUD phenotypic definitions (e.g., quantity of use, problem-oriented) and data collection instruments (self-report or clinician administered) that are both practical and efficient to collect, and likely to provide important insights concerning prevention, intervention, and medication development. Conclusions reached by the panel included optimism about the successes that have occurred in the existing family studies ascertained to include densely affected pedigrees. Evaluation of methodologies led, overall, to a panel consensus that steps should be taken to utilize biobank collection in conjunction with family-based investigations for optimal variant discovery.