Browsing by Author "Kranzler, Henry R."

Now showing 1 - 10 of 22
  • Thumbnail Image
    Item
    A multiancestry genome-wide association study of unexplained chronic ALT elevation as a proxy for nonalcoholic fatty liver disease with histological and radiological validation
    (Springer Nature, 2022) Vujkovic, Marijana; Ramdas, Shweta; Lorenz, Kim M.; Guo, Xiuqing; Darlay, Rebecca; Cordell, Heather J.; He, Jing; Gindin, Yevgeniy; Chung, Chuhan; Myers, Robert P.; Schneider, Carolin V.; Park, Joseph; Lee, Kyung Min; Serper, Marina; Carr, Rotonya M.; Kaplan, David E.; Haas, Mary E.; MacLean, Matthew T.; Witschey, Walter R.; Zhu, Xiang; Tcheandjieu, Catherine; Kember, Rachel L.; Kranzler, Henry R.; Verma, Anurag; Giri, Ayush; Klarin, Derek M.; Sun, Yan V.; Huang, Jie; Huffman, Jennifer E.; Townsend Creasy, Kate; Hand, Nicholas J.; Liu, Ching-Ti; Long, Michelle T.; Yao, Jie; Budoff, Matthew; Tan, Jingyi; Li, Xiaohui; Lin, Henry J.; Chen, Yii-Der Ida; Taylor, Kent D.; Chang, Ruey-Kang; Krauss, Ronald M.; Vilarinho, Silvia; Brancale, Joseph; Nielsen, Jonas B.; Locke, Adam E.; Jones, Marcus B.; Verweij, Niek; Baras, Aris; Reddy, K. Rajender; Neuschwander-Tetri, Brent A.; Schwimmer, Jeffrey B.; Sanyal, Arun J.; Chalasani, Naga; Ryan, Kathleen A.; Mitchell, Braxton D.; Gill, Dipender; Wells, Andrew D.; Manduchi, Elisabetta; Saiman, Yedidya; Mahmud, Nadim; Miller, Donald R.; Reaven, Peter D.; Phillips, Lawrence S.; Muralidhar, Sumitra; DuVall, Scott L.; Lee, Jennifer S.; Assimes, Themistocles L.; Pyarajan, Saiju; Cho, Kelly; Edwards, Todd L.; Damrauer, Scott M.; Wilson, Peter W.; Gaziano, J. Michael; O'Donnell, Christopher J.; Khera, Amit V.; Grant, Struan F. A.; Brown, Christopher D.; Tsao, Philip S.; Saleheen, Danish; Lotta, Luca A.; Bastarache, Lisa; Anstee, Quentin M.; Daly, Ann K.; Meigs, James B.; Rotter, Jerome I.; Lynch, Julie A.; Regeneron Genetics Center; Geisinger-Regeneron DiscovEHR Collaboration; EPoS Consortium; VA Million Veteran Program; Rader, Daniel J.; Voight, Benjamin F.; Chang, Kyong-Mi; Medicine, School of Medicine
    Nonalcoholic fatty liver disease (NAFLD) is a growing cause of chronic liver disease. Using a proxy NAFLD definition of chronic elevation of alanine aminotransferase (cALT) levels without other liver diseases, we performed a multiancestry genome-wide association study (GWAS) in the Million Veteran Program (MVP) including 90,408 cALT cases and 128,187 controls. Seventy-seven loci exceeded genome-wide significance, including 25 without prior NAFLD or alanine aminotransferase associations, with one additional locus identified in European American-only and two in African American-only analyses (P < 5 × 10-8). External replication in histology-defined NAFLD cohorts (7,397 cases and 56,785 controls) or radiologic imaging cohorts (n = 44,289) replicated 17 single-nucleotide polymorphisms (SNPs) (P < 6.5 × 10-4), of which 9 were new (TRIB1, PPARG, MTTP, SERPINA1, FTO, IL1RN, COBLL1, APOH and IFI30). Pleiotropy analysis showed that 61 of 77 multiancestry and all 17 replicated SNPs were jointly associated with metabolic and/or inflammatory traits, revealing a complex model of genetic architecture. Our approach integrating cALT, histology and imaging reveals new insights into genetic liability to NAFLD.
  • Thumbnail Image
    Item
    Ancestry May Confound Genetic Machine Learning: Candidate-Gene Prediction of Opioid Use Disorder as an Example
    (Elsevier, 2021) Hatoum, Alexander S.; Wendt, Frank R.; Galimberti, Marco; Polimanti, Renato; Neale, Benjamin; Kranzler, Henry R.; Gelernter, Joel; Edenberg, Howard J.; Agrawal, Arpana; Medical and Molecular Genetics, School of Medicine
    Background: Machine learning (ML) models are beginning to proliferate in psychiatry, however machine learning models in psychiatric genetics have not always accounted for ancestry. Using an empirical example of a proposed genetic test for OUD, and exploring a similar test for tobacco dependence and a simulated binary phenotype, we show that genetic prediction using ML is vulnerable to ancestral confounding. Methods: We utilize five ML algorithms trained with 16 brain reward-derived "candidate" SNPs proposed for commercial use and examine their ability to predict OUD vs. ancestry in an out-of-sample test set (N = 1000, stratified into equal groups of n = 250 cases and controls each of European and African ancestry). We rerun analyses with 8 random sets of allele-frequency matched SNPs. We contrast findings with 11 genome-wide significant variants for tobacco smoking. To document generalizability, we generate and test a random phenotype. Results: None of the 5 ML algorithms predict OUD better than chance when ancestry was balanced but were confounded with ancestry in an out-of-sample test. In addition, the algorithms preferentially predicted admixed subpopulations. Random sets of variants matched to the candidate SNPs by allele frequency produced similar bias. Genome-wide significant tobacco smoking variants were also confounded by ancestry. Finally, random SNPs predicting a random simulated phenotype show that the bias attributable to ancestral confounding could impact any ML-based genetic prediction. Conclusions: Researchers and clinicians are encouraged to be skeptical of claims of high prediction accuracy from ML-derived genetic algorithms for polygenic traits like addiction, particularly when using candidate variants.
  • Thumbnail Image
    Item
    Association of the OPRM1 Variant rs1799971 (A118G) with Non-Specific Liability to Substance Dependence in a Collaborative de novo Meta-Analysis of European-Ancestry Cohorts
    (Springer, 2016-03) Schwantes-An, Tae-Hwi; Zhang, Juan; Chen, Li-Shiun; Hartz, Sarah M.; Culverhouse, Robert C.; Chen, Xiangning; Coon, Hilary; Frank, Josef; Kamens, Helen M.; Konte, Bettina; Kovanen, Leena; Latvala, Antti; Legrand, Lisa N.; Maher, Brion S.; Melroy, Whitney E.; Nelson, Elliot C.; Reid, Mark W.; Robinson, Jason D.; Shen, Pei-Hong; Yang, Bao-Zhu; Andrews, Judy A.; Aveyard, Paul; Beltcheva, Olga; Brown, Sandra A.; Cannon, Dale S.; Cichon, Sven; Corley, Robin P.; Dahmen, Norbert; Degenhardt, Louisa; Foroud, Tatiana; Gaebel, Wolfgang; Giegling, Ina; Glatt, Stephen J.; Grucza, Richard A.; Hardin, Jill; Hartmann, Annette M.; Heath, Andrew C.; Herms, Stefan; Hodgkinson, Colin A.; Hoffmann, Per; Hops, Hyman; Huizinga, David; Ising, Marcus; Johnson, Eric O.; Johnstone, Elaine; Kaneva, Radka P.; Kendler, Kenneth S.; Kiefer, Falk; Kranzler, Henry R.; Krauter, Ken S.; Levran, Orna; Lucae, Susanne; Lynskey, Michael T.; Maier, Wolfgang; Mann, Karl; Martin, Nicholas G.; Mattheisen, Manuel; Montgomery, Grant W.; Müller-Myhsok, Bertram; Murphy, Michael F.; Neale, Michael C.; Nikolov, Momchil A.; Nishita, Denise; Nöthen, Markus M.; Nurnberger, John; Partonen, Timo; Pergadia, Michele L.; Reynolds, Maureen; Ridinger, Monika; Rose, Richard J.; Rouvinen-Lagerström, Noora; Scherbaum, Norbert; Schmäl, Christine; Soyka, Michael; Stallings, Michael C.; Steffens, Michael; Treutlein, Jens; Tsuang, Ming; Wallace, Tamara L.; Wodarz, Norbert; Yuferov, Vadim; Zill, Peter; Bergen, Andrew W.; Chen, Jingchun; Cinciripini, Paul M.; Edenberg, Howard J.; Ehringer, Marissa A.; Ferrell, Robert E.; Gelernter, Joel; Goldman, David; Hewitt, John K.; Hopfer, Christian J.; Iacono, William G.; Kaprio, Jaakko; Kreek, Mary Jeanne; Kremensky, Ivo M.; Madden, Pamela A.F.; McGue, Matt; Munafò, Marcus R.; Philibert, Robert A.; Rietschel, Marcella; Roy, Alec; Rujescu, Dan; Saarikoski, Sirkku T.; Swan, Gary E.; Todorov, Alexandre A.; Vanyukov, Michael M.; Weiss, Robert B.; Bierut, Laura J.; Saccone, Nancy L.; Department of Medical & Molecular Genetics, IU School of Medicine
    The mu1 opioid receptor gene, OPRM1, has long been a high-priority candidate for human genetic studies of addiction. Because of its potential functional significance, the non-synonymous variant rs1799971 (A118G, Asn40Asp) in OPRM1 has been extensively studied, yet its role in addiction has remained unclear, with conflicting association findings. To resolve the question of what effect, if any, rs1799971 has on substance dependence risk, we conducted collaborative meta-analyses of 25 datasets with over 28,000 European-ancestry subjects. We investigated non-specific risk for "general" substance dependence, comparing cases dependent on any substance to controls who were non-dependent on all assessed substances. We also examined five specific substance dependence diagnoses: DSM-IV alcohol, opioid, cannabis, and cocaine dependence, and nicotine dependence defined by the proxy of heavy/light smoking (cigarettes-per-day >20 vs. ≤ 10). The G allele showed a modest protective effect on general substance dependence (OR = 0.90, 95% C.I. [0.83-0.97], p value = 0.0095, N = 16,908). We observed similar effects for each individual substance, although these were not statistically significant, likely because of reduced sample sizes. We conclude that rs1799971 contributes to mechanisms of addiction liability that are shared across different addictive substances. This project highlights the benefits of examining addictive behaviors collectively and the power of collaborative data sharing and meta-analyses.
  • Thumbnail Image
    Item
    Candidate Genes from an FDA-Approved Algorithm Fail to Predict Opioid Use Disorder Risk in Over 450,000 Veterans
    (medRxiv, 2024-05-16) Davis, Christal N.; Jinwala, Zeal; Hatoum, Alexander S.; Toikumo, Sylvanus; Agrawal, Arpana; Rentsch, Christopher T.; Edenberg, Howard J.; Baurley, James W.; Hartwell, Emily E.; Crist, Richard C.; Gray, Joshua C.; Justice, Amy C.; Gelernter, Joel; Kember, Rachel L.; Kranzler, Henry R.; Biochemistry and Molecular Biology, School of Medicine
    Importance: Recently, the Food and Drug Administration gave pre-marketing approval to algorithm based on its purported ability to identify genetic risk for opioid use disorder. However, the clinical utility of the candidate genes comprising the algorithm has not been independently demonstrated. Objective: To assess the utility of 15 variants in candidate genes from an algorithm intended to predict opioid use disorder risk. Design: This case-control study examined the association of 15 candidate genetic variants with risk of opioid use disorder using available electronic health record data from December 20, 1992 to September 30, 2022. Setting: Electronic health record data, including pharmacy records, from Million Veteran Program participants across the United States. Participants: Participants were opioid-exposed individuals enrolled in the Million Veteran Program (n = 452,664). Opioid use disorder cases were identified using International Classification of Disease diagnostic codes, and controls were individuals with no opioid use disorder diagnosis. Exposures: Number of risk alleles present across 15 candidate genetic variants. Main outcome and measures: Predictive performance of 15 genetic variants for opioid use disorder risk assessed via logistic regression and machine learning models. Results: Opioid exposed individuals (n=33,669 cases) were on average 61.15 (SD = 13.37) years old, 90.46% male, and had varied genetic similarity to global reference panels. Collectively, the 15 candidate genetic variants accounted for 0.4% of variation in opioid use disorder risk. The accuracy of the ensemble machine learning model using the 15 genes as predictors was 52.8% (95% CI = 52.1 - 53.6%) in an independent testing sample. Conclusions and relevance: Candidate genes that comprise the approved algorithm do not meet reasonable standards of efficacy in predicting opioid use disorder risk. Given the algorithm's limited predictive accuracy, its use in clinical care would lead to high rates of false positive and negative findings. More clinically useful models are needed to identify individuals at risk of developing opioid use disorder.
  • Thumbnail Image
    Item
    Genome-wide association analyses identify 95 risk loci and provide insights into the neurobiology of post-traumatic stress disorder
    (Springer Nature, 2024) Nievergelt, Caroline M.; Maihofer, Adam X.; Atkinson, Elizabeth G.; Chen, Chia-Yen; Choi, Karmel W.; Coleman, Jonathan R. I.; Daskalakis, Nikolaos P.; Duncan, Laramie E.; Polimanti, Renato; Aaronson, Cindy; Amstadter, Ananda B.; Andersen, Soren B.; Andreassen, Ole A.; Arbisi, Paul A.; Ashley-Koch, Allison E.; Austin, S. Bryn; Avdibegoviç, Esmina; Babić, Dragan; Bacanu, Silviu-Alin; Baker, Dewleen G.; Batzler, Anthony; Beckham, Jean C.; Belangero, Sintia; Benjet, Corina; Bergner, Carisa; Bierer, Linda M.; Biernacka, Joanna M.; Bierut, Laura J.; Bisson, Jonathan I.; Boks, Marco P.; Bolger, Elizabeth A.; Brandolino, Amber; Breen, Gerome; Bressan, Rodrigo Affonseca; Bryant, Richard A.; Bustamante, Angela C.; Bybjerg-Grauholm, Jonas; Bækvad-Hansen, Marie; Børglum, Anders D.; Børte, Sigrid; Cahn, Leah; Calabrese, Joseph R.; Caldas-de-Almeida, Jose Miguel; Chatzinakos, Chris; Cheema, Sheraz; Clouston, Sean A. P.; Colodro-Conde, Lucía; Coombes, Brandon J.; Cruz-Fuentes, Carlos S.; Dale, Anders M.; Dalvie, Shareefa; Davis, Lea K.; Deckert, Jürgen; Delahanty, Douglas L.; Dennis, Michelle F.; Desarnaud, Frank; DiPietro, Christopher P.; Disner, Seth G.; Docherty, Anna R.; Domschke, Katharina; Dyb, Grete; Džubur Kulenović, Alma; Edenberg, Howard J.; Evans, Alexandra; Fabbri, Chiara; Fani, Negar; Farrer, Lindsay A.; Feder, Adriana; Feeny, Norah C.; Flory, Janine D.; Forbes, David; Franz, Carol E.; Galea, Sandro; Garrett, Melanie E.; Gelaye, Bizu; Gelernter, Joel; Geuze, Elbert; Gillespie, Charles F.; Goleva, Slavina B.; Gordon, Scott D.; Goçi, Aferdita; Grasser, Lana Ruvolo; Guindalini, Camila; Haas, Magali; Hagenaars, Saskia; Hauser, Michael A.; Heath, Andrew C.; Hemmings, Sian M. J.; Hesselbrock, Victor; Hickie, Ian B.; Hogan, Kelleigh; Hougaard, David Michael; Huang, Hailiang; Huckins, Laura M.; Hveem, Kristian; Jakovljević, Miro; Javanbakht, Arash; Jenkins, Gregory D.; Johnson, Jessica; Jones, Ian; Jovanovic, Tanja; Karstoft, Karen-Inge; Kaufman, Milissa L.; Kennedy, James L.; Kessler, Ronald C.; Khan, Alaptagin; Kimbrel, Nathan A.; King, Anthony P.; Koen, Nastassja; Kotov, Roman; Kranzler, Henry R.; Krebs, Kristi; Kremen, William S.; Kuan, Pei-Fen; Lawford, Bruce R.; Lebois, Lauren A. M.; Lehto, Kelli; Levey, Daniel F.; Lewis, Catrin; Liberzon, Israel; Linnstaedt, Sarah D.; Logue, Mark W.; Lori, Adriana; Lu, Yi; Luft, Benjamin J.; Lupto, Michelle K.; Luykx, Jurjen J.; Makotkine, Iouri; Maples-Keller, Jessica L.; Marchese, Shelby; Marmar, Charles; Martin, Nicholas G.; Martínez-Levy, Gabriela A.; McAloney, Kerrie; McFarlane, Alexander; McLaughlin, Katie A.; McLean, Samuel A.; Medland, Sarah E.; Mehta, Divya; Meyers, Jacquelyn; Michopoulos, Vasiliki; Mikita, Elizabeth A.; Milani, Lili; Milberg, William; Miller, Mark W.; Morey, Rajendra A.; Morris, Charles Phillip; Mors, Ole; Mortensen, Preben Bo; Mufford, Mary S.; Nelson, Elliot C.; Nordentoft, Merete; Norman, Sonya B.; Nugent, Nicole R.; O'Donnell, Meaghan; Orcutt, Holly K.; Pan, Pedro M.; Panizzon, Matthew S.; Pathak, Gita A.; Peters, Edward S.; Peterson, Alan L.; Peverill, Matthew; Pietrzak, Robert H.; Polusny, Melissa A.; Porjesz, Bernice; Powers, Abigail; Qin, Xue-Jun; Ratanatharathorn, Andrew; Risbrough, Victoria B.; Roberts, Andrea L.; Rothbaum, Alex O.; Rothbaum, Barbara O.; Roy-Byrne, Peter; Ruggiero, Kenneth J.; Rung, Ariane; Runz, Heiko; Rutten, Bart P. F.; Saenz de Viteri, Stacey; Salum, Giovanni Abrahão; Sampson, Laura; Sanchez, Sixto E.; Santoro, Marcos; Seah, Carina; Seedat, Soraya; Seng, Julia S.; Shabalin, Andrey; Sheerin, Christina M.; Silove, Derrick; Smith, Alicia K.; Smoller, Jordan W.; Sponheim, Scott R.; Stein, Dan J.; Stensland, Synne; Stevens, Jennifer S.; Sumner, Jennifer A.; Teicher, Martin H.; Thompson, Wesley K.; Tiwari, Arun K.; Trapido, Edward; Uddin, Monica; Ursano, Robert J.; Valdimarsdóttir, Unnur; Van Hooff, Miranda; Vermetten, Eric; Vinkers, Christiaan H.; Voisey, Joanne; Wang, Yunpeng; Wang, Zhewu; Waszczuk, Monika; Weber, Heike; Wendt, Frank R.; Werge, Thomas; Williams, Michelle A.; Williamson, Douglas E.; Winsvold, Bendik S.; Winternitz, Sherry; Wolf, Christiane; Wolf, Erika J.; Xia, Yan; Xiong, Ying; Yehuda, Rachel; Young, Keith A.; Young, Ross McD.; Zai, Clement C.; Zai, Gwyneth C.; Zervas, Mark; Zhao, Hongyu; Zoellner, Lori A.; Zwart, John-Anker; deRoon-Cassini, Terri; van Rooij, Sanne J. H.; van den Heuvel, Leigh L.; AURORA Study; Estonian Biobank Research Team; FinnGen Investigators; HUNT All-In Psychiatry; Stein, Murray B.; Ressler, Kerry J.; Koenen, Karestan C.; Biochemistry and Molecular Biology, School of Medicine
    Post-traumatic stress disorder (PTSD) genetics are characterized by lower discoverability than most other psychiatric disorders. The contribution to biological understanding from previous genetic studies has thus been limited. We performed a multi-ancestry meta-analysis of genome-wide association studies across 1,222,882 individuals of European ancestry (137,136 cases) and 58,051 admixed individuals with African and Native American ancestry (13,624 cases). We identified 95 genome-wide significant loci (80 new). Convergent multi-omic approaches identified 43 potential causal genes, broadly classified as neurotransmitter and ion channel synaptic modulators (for example, GRIA1, GRM8 and CACNA1E), developmental, axon guidance and transcription factors (for example, FOXP2, EFNA5 and DCC), synaptic structure and function genes (for example, PCLO, NCAM1 and PDE4B) and endocrine or immune regulators (for example, ESR1, TRAF3 and TANK). Additional top genes influence stress, immune, fear and threat-related processes, previously hypothesized to underlie PTSD neurobiology. These findings strengthen our understanding of neurobiological systems relevant to PTSD pathophysiology, while also opening new areas for investigation.
  • Thumbnail Image
    Item
    Genome-wide association study in individuals of European and African ancestry and multi-trait analysis of opioid use disorder identifies 19 independent genome-wide significant risk loci
    (Springer, 2022-10) Deak, Joseph D.; Zhou, Hang; Galimberti, Marco; Levey, Daniel F.; Wendt, Frank R.; Sanchez-Roige, Sandra; Hatoum, Alexander S.; Johnson, Emma C.; Nunez, Yaira Z.; Demontis, Ditte; Børglum, Anders D.; Rajagopal, Veera M.; Jennings, Mariela V.; Kember, Rachel L.; Justice, Amy C.; Edenberg, Howard J.; Agrawal, Arpana; Polimanti, Renato; Kranzler, Henry R.; Gelernter, Joel; Biochemistry and Molecular Biology, School of Medicine
    Despite the large toll of opioid use disorder (OUD), genome-wide association studies (GWAS) of OUD to date have yielded few susceptibility loci. We performed a large-scale GWAS of OUD in individuals of European (EUR) and African (AFR) ancestry, optimizing genetic informativeness by performing MTAG (Multi-trait analysis of GWAS) with genetically correlated substance use disorders (SUDs). Meta-analysis included seven cohorts: the Million Veteran Program, Psychiatric Genomics Consortium, iPSYCH, FinnGen, Partners Biobank, BioVU, and Yale-Penn 3, resulting in a total N = 639,063 (Ncases = 20,686;Neffective = 77,026) across ancestries. OUD cases were defined as having a lifetime OUD diagnosis, and controls as anyone not known to meet OUD criteria. We estimated SNP-heritability (h2SNP) and genetic correlations (rg). Based on genetic correlation, we performed MTAG on OUD, alcohol use disorder (AUD), and cannabis use disorder (CanUD). A leave-one-out polygenic risk score (PRS) analysis was performed to compare OUD and OUD-MTAG PRS as predictors of OUD case status in Yale-Penn 3. The EUR meta-analysis identified three genome-wide significant (GWS; p ≤ 5 × 10−8) lead SNPs—one at FURIN (rs11372849; p = 9.54 × 10−10) and two OPRM1 variants (rs1799971, p = 4.92 × 10−09; rs79704991, p = 1.11 × 10−08; r2 = 0.02). Rs1799971 (p = 4.91 × 10−08) and another OPRM1 variant (rs9478500; p = 1.95 × 10−08; r2 = 0.03) were identified in the cross-ancestry meta-analysis. Estimated h2SNP was 12.75%, with strong rg with CanUD (rg = 0.82; p = 1.14 × 10−47) and AUD (rg = 0.77; p = 6.36 × 10−78). The OUD-MTAG resulted in a GWAS Nequivalent = 128,748 and 18 independent GWS loci, some mapping to genes or gene regions that have previously been associated with psychiatric or addiction phenotypes. The OUD-MTAG PRS accounted for 3.81% of OUD variance (beta = 0.61;s.e. = 0.066; p = 2.00 × 10−16) compared to 2.41% (beta = 0.45; s.e. = 0.058; p = 2.90 × 10−13) explained by the OUD PRS. The current study identified OUD variant associations at OPRM1, single variant associations with FURIN, and 18 GWS associations in the OUD-MTAG. The genetic architecture of OUD is likely influenced by both OUD-specific loci and loci shared across SUDs.
  • Thumbnail Image
    Item
    Genome-wide association study of more than 40,000 bipolar disorder cases provides new insights into the underlying biology
    (Springer Nature, 2021-06) Mullins, Niamh; Forstner, Andreas J.; O'Connell, Kevin S.; Coombes, Brandon; Coleman, Jonathan R.I.; Qiao, Zhen; Als, Thomas D.; Bigdeli, Tim B.; Børte, Sigrid; Bryois, Julien; Charney, Alexander W.; Drange, Ole Kristian; Gandal, Michael J.; Hagenaars, Saskia P.; Ikeda, Masashi; Kamitaki, Nolan; Kim, Minsoo; Krebs, Kristi; Panagiotaropoulou, Georgia; Schilder, Brian M.; Sloofman, Laura G.; Steinberg, Stacy; Trubetskoy, Vassily; Winsvold, Bendik S.; Won, Hong-Hee; Abramova, Liliya; Adorjan, Kristina; Agerbo, Esben; Al Eissa, Mariam; Albani, Diego; Alliey-Rodriguez, Ney; Anjorin, Adebayo; Antilla, Verneri; Antoniou, Anastasia; Awasthi, Swapnil; Baek, Ji Hyun; Bækvad-Hansen, Marie; Bass, Nicholas; Bauer, Michael; Beins, Eva C.; Bergen, Sarah E.; Birner, Armin; Pedersen, Carsten Bøcker; Bøen, Erlend; Boks, Marco P.; Bosch, Rosa; Brum, Murielle; Brumpton, Ben M.; Brunkhorst-Kanaan, Nathalie; Budde, Monika; Bybjerg-Grauholm, Jonas; Byerley, William; Cairns, Murray; Casas, Miquel; Cervantes, Pablo; Clarke, Toni-Kim; Cruceanu, Cristiana; Cuellar-Barboza, Alfredo; Cunningham, Julie; Curtis, David; Czerski, Piotr M.; Dale, Anders M.; Dalkner, Nina; David, Friederike S.; Degenhardt, Franziska; Djurovic, Srdjan; Dobbyn, Amanda L.; Douzenis, Athanassios; Elvsåshagen, Torbjørn; Escott-Price, Valentina; Ferrier, I. Nicol; Fiorentino, Alessia; Foroud, Tatiana M.; Forty, Liz; Frank, Josef; Frei, Oleksandr; Freimer, Nelson B.; Frisén, Louise; Gade, Katrin; Garnham, Julie; Gelernter, Joel; Pedersen, Marianne Giørtz; Gizer, Ian R.; Gordon, Scott D.; Gordon-Smith, Katherine; Greenwood, Tiffany A.; Grove, Jakob; Guzman-Parra, José; Ha, Kyooseob; Haraldsson, Magnus; Hautzinger, Martin; Heilbronner, Urs; Hellgren, Dennis; Herms, Stefan; Hoffmann, Per; Holmans, Peter A.; Huckins, Laura; Jamain, Stéphane; Johnson, Jessica S.; Kalman, Janos L.; Kamatani, Yoichiro; Kennedy, James L.; Kittel-Schneider, Sarah; Knowles, James A.; Kogevinas, Manolis; Koromina, Maria; Kranz, Thorsten M.; Kranzler, Henry R.; Kubo, Michiaki; Kupka, Ralph; Kushner, Steven A.; Lavebratt, Catharina; Lawrence, Jacob; Leber, Markus; Lee, Heon-Jeong; Lee, Phil H.; Levy, Shawn E.; Lewis, Catrin; Liao, Calwing; Lucae, Susanne; Lundberg, Martin; MacIntyre, Donald J.; Magnusson, Sigurdur H.; Maier, Wolfgang; Maihofer, Adam; Malaspina, Dolores; Maratou, Eirini; Martinsson, Lina; Mattheisen, Manuel; McCarroll, Steven A.; McGregor, Nathaniel W.; McGuffin, Peter; McKay, James D.; Medeiros, Helena; Medland, Sarah E.; Millischer, Vincent; Montgomery, Grant W.; Moran, Jennifer L.; Morris, Derek W.; Mühleisen, Thomas W.; O'Brien, Niamh; O'Donovan, Claire; Loohuis, Loes M. Olde; Oruc, Lilijana; Papiol, Sergi; Pardiñas, Antonio F.; Perry, Amy; Pfennig, Andrea; Porichi, Evgenia; Potash, James B.; Quested, Digby; Raj, Towfique; Rapaport, Mark H.; DePaulo, J. Raymond; Regeer, Eline J.; Rice, John P.; Rivas, Fabio; Rivera, Margarita; Roth, Julian; Roussos, Panos; Ruderfer, Douglas M.; Sánchez-Mora, Cristina; Schulte, Eva C.; Senner, Fanny; Sharp, Sally; Shilling, Paul D.; Sigurdsson, Engilbert; Sirignano, Lea; Slaney, Claire; Smeland, Olav B.; Smith, Daniel J.; Sobell, Janet L.; Søholm Hansen, Christine; Artigas, Maria Soler; Spijker, Anne T.; Stein, Dan J.; Strauss, John S.; Świątkowska, Beata; Terao, Chikashi; Thorgeirsson, Thorgeir E.; Toma, Claudio; Tooney, Paul; Tsermpini, Evangelia-Eirini; Vawter, Marquis P.; Vedder, Helmut; Walters, James T.R.; Witt, Stephanie H.; Xi, Simon; Xu, Wei; Yang, Jessica Mei Kay; Young, Allan H.; Young, Hannah; Zandi, Peter P.; Zhou, Hang; Zillich, Lea; Adolfsson, Rolf; Agartz, Ingrid; Alda, Martin; Alfredsson, Lars; Babadjanova, Gulja; Backlund, Lena; Baune, Bernhard T.; Bellivier, Frank; Bengesser, Susanne; Berrettini, Wade H.; Blackwood, Douglas H.R.; Boehnke, Michael; Børglum, Anders D.; Breen, Gerome; Carr, Vaughan J.; Catts, Stanley; Corvin, Aiden; Craddock, Nicholas; Dannlowski, Udo; Dikeos, Dimitris; Esko, Tõnu; Etain, Bruno; Ferentinos, Panagiotis; Frye, Mark; Fullerton, Janice M.; Gawlik, Micha; Gershon, Elliot S.; Goes, Fernando S.; Green, Melissa J.; Grigoroiu-Serbanescu, Maria; Hauser, Joanna; Henskens, Frans; Hillert, Jan; Hong, Kyung Sue; Hougaard, David M.; Hultman, Christina M.; Hveem, Kristian; Iwata, Nakao; Jablensky, Assen V.; Jones, Ian; Jones, Lisa A.; Kahn, René S.; Kelsoe, John R.; Kirov, George; Landén, Mikael; Leboyer, Marion; Lewis, Cathryn M.; Li, Qingqin S.; Lissowska, Jolanta; Lochner, Christine; Loughland, Carmel; Martin, Nicholas G.; Mathews, Carol A.; Mayoral, Fermin; McElroy, Susan L.; McIntosh, Andrew M.; McMahon, Francis J.; Melle, Ingrid; Michie, Patricia; Milani, Lili; Mitchell, Philip B.; Morken, Gunnar; Mors, Ole; Mortensen, Preben Bo; Mowry, Bryan; Müller-Myhsok, Bertram; Myers, Richard M.; Neale, Benjamin M.; Nievergelt, Caroline M.; Nordentoft, Merete; Nöthen, Markus M.; O'Donovan, Michael C.; Oedegaard, Ketil J.; Olsson, Tomas; Owen, Michael J.; Paciga, Sara A.; Pantelis, Chris; Pato, Carlos; Pato, Michele T.; Patrinos, George P.; Perlis, Roy H.; Posthuma, Danielle; Ramos-Quiroga, Josep Antoni; Reif, Andreas; Reininghaus, Eva Z.; Ribasés, Marta; Rietschel, Marcella; Ripke, Stephan; Rouleau, Guy A.; Saito, Takeo; Schall, Ulrich; Schalling, Martin; Schofield, Peter R.; Schulze, Thomas G.; Scott, Laura J.; Scott, Rodney J.; Serretti, Alessandro; Weickert, Cynthia Shannon; Smoller, Jordan W.; Stefansson, Hreinn; Stefansson, Kari; Stordal, Eystein; Streit, Fabian; Sullivan, Patrick F.; Turecki, Gustavo; Vaaler, Arne E.; Vieta, Eduard; Vincent, John B.; Waldman, Irwin D.; Weickert, Thomas W.; Werge, Thomas; Wray, Naomi R.; Zwart, John-Anker; Biernacka, Joanna M.; Nurnberger, John I.; Cichon, Sven; Edenberg, Howard J.; Stahl, Eli A.; McQuillin, Andrew; Florio, Arianna Di; Ophoff, Roel A.; Andreassen, Ole A.; Medical and Molecular Genetics, School of Medicine
    Bipolar disorder is a heritable mental illness with complex etiology. We performed a genome-wide association study of 41,917 bipolar disorder cases and 371,549 controls of European ancestry, which identified 64 associated genomic loci. Bipolar disorder risk alleles were enriched in genes in synaptic signaling pathways and brain-expressed genes, particularly those with high specificity of expression in neurons of the prefrontal cortex and hippocampus. Significant signal enrichment was found in genes encoding targets of antipsychotics, calcium channel blockers, antiepileptics and anesthetics. Integrating expression quantitative trait locus data implicated 15 genes robustly linked to bipolar disorder via gene expression, encoding druggable targets such as HTR6, MCHR1, DCLK3 and FURIN. Analyses of bipolar disorder subtypes indicated high but imperfect genetic correlation between bipolar disorder type I and II and identified additional associated loci. Together, these results advance our understanding of the biological etiology of bipolar disorder, identify novel therapeutic leads and prioritize genes for functional follow-up studies.
  • Thumbnail Image
    Item
    Genome-wide association study of phenotypes measuring progression from first cocaine or opioid use to dependence reveals novel risk genes
    (Open Exploration, 2021) Sherva, Richard; Zhu, Congcong; Wetherill, Leah; Edenberg, Howard J.; Johnson, Emma; Degenhardt, Louisa; Agrawal, Arpana; Martin, Nicholas G.; Nelson, Elliot; Kranzler, Henry R.; Gelernter, Joel; Farrer, Lindsay A.; Medical and Molecular Genetics, School of Medicine
    Aim: Substance use disorders (SUD) result in substantial morbidity and mortality worldwide. Opioids, and to a lesser extent cocaine, contribute to a large percentage of this health burden. Despite their high heritability, few genetic risk loci have been identified for either opioid or cocaine dependence (OD or CD, respectively). A genome-wide association study of OD and CD related phenotypes reflecting the time between first self-reported use of these substances and a first DSM-IV dependence diagnosis was conducted. Methods: Cox proportional hazards regression in a discovery sample of 6,188 African-Americans (AAs) and 6,835 European-Americans (EAs) participants in a genetic study of multiple substance dependence phenotypes were used to test for association between genetic variants and these outcomes. The top findings were tested for replication in two independent cohorts. Results: In the discovery sample, three independent regions containing variants associated with time to dependence at P < 5 x 10-8 were identified, one (rs61835088 = 1.03 x 10-8) for cocaine in the combined EA-AA meta-analysis in the gene FAM78B on chromosome 1, and two for opioids in the AA portion of the sample in intergenic regions of chromosomes 4 (rs4860439, P = 1.37 x 10-8) and 9 (rs7032521, P = 3.30 x 10-8). After meta-analysis with data from the replication cohorts, the signal at rs61835088 improved (HR = 0.87, P = 3.71 x 10-9 and an intergenic SNP on chromosome 21 (rs2825295, HR = 1.14, P = 2.57 x 10-8) that missed the significance threshold in the AA discovery sample became genome-wide significant (GWS) for CD. Conclusions: Although the two GWS variants are not in genes with obvious links to SUD biology and have modest effect sizes, they are statistically robust and show evidence for association in independent samples. These results may point to novel pathways contributing to disease progression and highlight the utility of related phenotypes to better understand the genetics of SUDs.
  • Thumbnail Image
    Item
    Genome-wide association study of stimulant dependence
    (Springer Nature, 2021-06-29) Cox, Jiayi; Sherva, Richard; Wetherill, Leah; Foroud, Tatiana; Edenberg, Howard J.; Kranzler, Henry R.; Gelernter, Joel; Farrer, Lindsay A.; Medical and Molecular Genetics, School of Medicine
    Stimulant dependence is heritable, but specific genetic factors underlying the trait have not been identified. A genome-wide association study for stimulant dependence was performed in a discovery cohort of African- (AA) and European-ancestry (EA) subjects ascertained for genetic studies of alcohol, opioid, and cocaine use disorders. The sample comprised individuals with DSM-IV stimulant dependence (393 EA cases, 5288 EA controls; 155 AA cases, 5603 AA controls). An independent cohort from the family-based Collaborative Study on the Genetics of Alcoholism (532 EA cases, 7635 EA controls; 53 AA cases, AA 3352 controls) was used for replication. One variant in SLC25A16 (rs2394476, p = 3.42 × 10-10, odds ratio [OR] = 3.70) was GWS in AAs. Four other loci showed suggestive evidence, including KCNA4 in AAs (rs11500237, p = 2.99 × 10-7, OR = 2.31) which encodes one of the potassium voltage-gated channel protein that has been linked to several other substance use disorders, and CPVL in the combined population groups (rs1176440, p = 3.05 × 10-7, OR = 1.35), whose expression was previously shown to be upregulated in the prefrontal cortex from users of cocaine, cannabis, and phencyclidine. Analysis of the top GWAS signals revealed a significant enrichment with nicotinic acetylcholine receptor genes (adjusted p = 0.04) and significant pleiotropy between stimulant dependence and alcohol dependence in EAs (padj = 3.6 × 10-3), an anxiety disorder in EAs (padj = 2.1 × 10-4), and ADHD in both AAs (padj = 3.0 × 10-33) and EAs (padj = 6.7 × 10-35). Our results implicate novel genes and pathways as having roles in the etiology of stimulant dependence.
  • Thumbnail Image
    Item
    Genome-wide meta-analysis of problematic alcohol use in 435,563 individuals yields insights into biology and relationships with other traits
    (Nature, 2020-07) Zhou, Hang; Sealock, Julia M.; Sanchez-Roige, Sandra; Clarke, Toni-Kim; Levey, Daniel F.; Cheng, Zhongshan; Li, Boyang; Polimanti, Renato; Kember, Rachel L.; Smith, Rachel Vickers; Thygesen, Johan H.; Morgan, Marsha Y.; Atkinson, Stephen R.; Thursz, Mark R.; Nyegaard, Mette; Mattheisen, Manuel; Børglum, Anders D.; Johnson, Emma C.; Justice, Amy C.; Palmer, Abraham A.; McQuillin, Andrew; Davis, Lea K.; Edenberg, Howard J.; Agrawal, Arpana; Kranzler, Henry R.; Gelernter, Joel; Medical and Molecular Genetics, School of Medicine
    Problematic alcohol use (PAU) is a leading cause of death and disability worldwide. Although genome-wide association studies have identified PAU risk genes, the genetic architecture of this trait is not fully understood. We conducted a proxy-phenotype meta-analysis of PAU, combining alcohol use disorder and problematic drinking, in 435,563 European-ancestry individuals. We identified 29 independent risk variants, 19 of them novel. PAU was genetically correlated with 138 phenotypes, including substance use and psychiatric traits. Phenome-wide polygenic risk score analysis in an independent biobank sample (BioVU, n = 67,589) confirmed the genetic correlations between PAU and substance use and psychiatric disorders. Genetic heritability of PAU was enriched in brain and in conserved and regulatory genomic regions. Mendelian randomization suggested causal effects on liability to PAU of substance use, psychiatric status, risk-taking behavior and cognitive performance. In summary, this large PAU meta-analysis identified novel risk loci and revealed genetic relationships with numerous other traits.