Browsing by Author "Rice, John P."
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Item Common biological networks underlie genetic risk for alcoholism in African- and European-American populations(Wiley, 2013) Kos, Mark Z.; Yan, Jia; Dick, Danielle M.; Agrawal, Arpana; Bucholz, Kathleen K.; Rice, John P.; Johnson, Eric O.; Schuckit, Marc; Kuperman, Sam; Kramer, John; Goate, Alison M.; Tischfield, Jay A.; Foroud, Tatiana; Nurnberger, John, Jr.; Hesselbrock, Victor; Porjesz, Bernice; Bierut, Laura J.; Edenberg, Howard J.; Almasy, Laura; Medical and Molecular Genetics, School of MedicineAlcohol dependence (AD) is a heritable substance addiction with adverse physical and psychological consequences, representing a major health and economic burden on societies worldwide. Genes thus far implicated via linkage, candidate gene and genome-wide association studies (GWAS) account for only a small fraction of its overall risk, with effects varying across ethnic groups. Here we investigate the genetic architecture of alcoholism and report on the extent to which common, genome-wide SNPs collectively account for risk of AD in two US populations, African-Americans (AAs) and European-Americans (EAs). Analyzing GWAS data for two independent case-control sample sets, we compute polymarker scores that are significantly associated with alcoholism (P = 1.64 × 10(-3) and 2.08 × 10(-4) for EAs and AAs, respectively), reflecting the small individual effects of thousands of variants derived from patterns of allelic architecture that are population specific. Simulations show that disease models based on rare and uncommon causal variants (MAF < 0.05) best fit the observed distribution of polymarker signals. When scoring bins were annotated for gene location and examined for constituent biological networks, gene enrichment is observed for several cellular processes and functions in both EA and AA populations, transcending their underlying allelic differences. Our results reveal key insights into the complex etiology of AD, raising the possibility of an important role for rare and uncommon variants, and identify polygenic mechanisms that encompass a spectrum of disease liability, with some, such as chloride transporters and glycine metabolism genes, displaying subtle, modifying effects that are likely to escape detection in most GWAS designs.Item CYP2A6 metabolism in the development of smoking behaviors in young adults(Wiley, 2018-01) Olfson, Emily; Bloom, Joseph; Bertelsen, Sarah; Budde, John P.; Breslau, Naomi; Brooks, Andrew; Culverhouse, Robert; Chan, Grace; Chen, Li-Shiun; Chorlian, David; Dick, Danielle M.; Edenberg, Howard J.; Hartz, Sarah; Hatsukami, Dorothy; Hesselbrock, Victor M.; Johnson, Eric O.; Kramer, John R.; Kuperman, Samuel; Meyers, Jacquelyn L.; Nurnberger, John; Porjesz, Bernice; Saccone, Nancy L.; Schuckit, Marc A.; Stitzel, Jerry; Tischfield, Jay A.; Rice, John P.; Goate, Alison; Bierut, Laura J.; Biochemistry and Molecular Biology, School of MedicineCytochrome P450 2A6 (CYP2A6) encodes the enzyme responsible for the majority of nicotine metabolism. Previous studies support that slow metabolizers smoke fewer cigarettes once nicotine dependent but provide conflicting results on the role of CYP2A6 in the development of dependence. By focusing on the critical period of young adulthood, this study examines the relationship of CYP2A6 variation and smoking milestones. A total of 1209 European American young adults enrolled in the Collaborative Study on the Genetics of Alcoholism were genotyped for CYP2A6 variants to calculate a previously well-validated metric that estimates nicotine metabolism. This metric was not associated with the transition from never smoking to smoking initiation nor with the transition from initiation to daily smoking (P > 0.4). But among young adults who had become daily smokers (n = 506), decreased metabolism was associated with increased risk of nicotine dependence (P = 0.03) (defined as Fagerström Test for Nicotine Dependence score ≥4). This finding was replicated in the Collaborative Genetic Study of Nicotine Dependence with 335 young adult daily smokers (P = 0.02). Secondary meta-analysis indicated that slow metabolizers had a 53 percent increased odds (OR = 1.53, 95 percent CI 1.11-2.11, P = 0.009) of developing nicotine dependence compared with normal metabolizers. Furthermore, secondary analyses examining four-level response of time to first cigarette after waking (>60, 31-60, 6-30, ≤5 minutes) demonstrated a robust effect of the metabolism metric in Collaborative Study on the Genetics of Alcoholism (P = 0.03) and Collaborative Genetic Study of Nicotine Dependence (P = 0.004), illustrating the important role of this measure of dependence. These findings highlight the complex role of CYP2A6 variation across different developmental stages of smoking behaviors.Item Description of the data from the Collaborative Study on the Genetics of Alcoholism (COGA) and single-nucleotide polymorphism genotyping for Genetic Analysis Workshop 14(Springer Nature, 2005-12-30) Edenberg, Howard J.; Bierut, Laura J.; Boyce, Paul; Cao, Manqiu; Cawley, Simon; Chiles, Richard; Doheny, Kimberly F.; Hansen, Mark; Hinrichs, Tony; Jones, Kevin; Kelleher, Mark; Kennedy, Giulia C.; Liu, Guoying; Marcus, Gregory; McBride, Celeste; Shaw Murray, Sarah; Oliphant, Arnold; Pettengill, James; Porjesz, Bernice; Pugh, Elizabeth W.; Rice, John P.; Rubano, Todd; Shannon, Stu; Steeke, Rhoberta; Tischfield, Jay A.; Tsai, Ya Yu; Zhang, Chun; Begleiter, Henri; Biochemistry and Molecular Biology, School of MedicineThe data provided to the Genetic Analysis Workshop 14 (GAW 14) was the result of a collaboration among several different groups, catalyzed by Elizabeth Pugh from The Center for Inherited Disease Research (CIDR) and the organizers of GAW 14, Jean MacCluer and Laura Almasy. The DNA, phenotypic characterization, and microsatellite genomic survey were provided by the Collaborative Study on the Genetics of Alcoholism (COGA), a nine-site national collaboration funded by the National Institute of Alcohol and Alcoholism (NIAAA) and the National Institute of Drug Abuse (NIDA) with the overarching goal of identifying and characterizing genes that affect the susceptibility to develop alcohol dependence and related phenotypes. CIDR, Affymetrix, and Illumina provided single-nucleotide polymorphism genotyping of a large subset of the COGA subjects. This article briefly describes the dataset that was provided.Item Development of Alcohol Use Disorder as a Function of Age, Severity, and Comorbidity with Externalizing and Internalizing Disorders in a Young Adult Cohort(Hapres Limited, 2019) Nurnberger Jr., John I.; Yang, Ziyi; Zang, Yong; Acion, Laura; Bierut, Laura; Bucholz, Kathleen; Chan, Grace; Dick, Danielle M.; Edenberg, Howard J.; Kramer, John; Kuperman, Samuel; Rice, John P.; Schuckit, Marc; Psychiatry, School of MedicineBackground: As part of the ongoing Collaborative Study of the Genetics of Alcoholism, we performed a longitudinal study of a high risk cohort of adolescents/young adults from families with a proband with an alcohol use disorder, along with a comparison group of age-matched controls. The intent was to compare the development of alcohol problems in subjects at risk with and without comorbid externalizing and internalizing psychiatric disorders. Methods: Subjects (N = 3286) were assessed with a structured psychiatric interview at 2 year intervals over 10 years (2004–2017). The age range at baseline was 12–21. Results: Subjects with externalizing disorders (with or without accompanying internalizing disorders) were at increased risk for the onset of an alcohol use disorder during the observation period. Subjects with internalizing disorders were at greater risk than those without comorbid disorders for onset of a moderate or severe alcohol use disorder. The statistical effect of comorbid disorders was greater in subjects with more severe alcohol use disorders. The developmental trajectory of drinking milestones and alcohol use disorders was also accelerated in those with more severe disorders. Conclusions: These results may be useful for counseling of subjects at risk who present for clinical care, especially those subjects manifesting externalizing and internalizing disorders in the context of a positive family history of an alcohol use disorder. We confirm and extend findings that drinking problems in subjects at greatest risk will begin in early adolescence.Item Dosage Transmission Disequilibrium Test (dTDT) for Linkage and Association Detection(Public Library of Science, 2013-05-14) Zhang, Zhehao; Wang, Jen-Chyong; Howells, William; Lin, Peng; Agrawal, Arpana; Edenberg, Howard J.; Tischfield, Jay A.; Schuckit, Marc A.; Bierut, Laura J.; Goate, Alison; Rice, John P.; Biochemistry and Molecular Biology, School of MedicineBoth linkage and association studies have been successfully applied to identify disease susceptibility genes with genetic markers such as microsatellites and Single Nucleotide Polymorphisms (SNPs). As one of the traditional family-based studies, the Transmission/Disequilibrium Test (TDT) measures the over-transmission of an allele in a trio from its heterozygous parents to the affected offspring and can be potentially useful to identify genetic determinants for complex disorders. However, there is reduced information when complete trio information is unavailable. In this study, we developed a novel approach to "infer" the transmission of SNPs by combining both the linkage and association data, which uses microsatellite markers from families informative for linkage together with SNP markers from the offspring who are genotyped for both linkage and a Genome-Wide Association Study (GWAS). We generalized the traditional TDT to process these inferred dosage probabilities, which we name as the dosage-TDT (dTDT). For evaluation purpose, we developed a simulation procedure to assess its operating characteristics. We applied the dTDT to the simulated data and documented the power of the dTDT under a number of different realistic scenarios. Finally, we applied our methods to a family study of alcohol dependence (COGA) and performed individual genotyping on complete families for the top signals. One SNP (rs4903712 on chromosome 14) remained significant after correcting for multiple testing Methods developed in this study can be adapted to other platforms and will have widespread applicability in genomic research when case-control GWAS data are collected in families with existing linkage data.Item Familial aggregation of postpartum mood symptoms in bipolar disorder pedigrees(Wiley, 2008-02) Payne, Jennifer L; MacKinnon, Dean F.; Mondimore, Francis M.; McInnis, Melvin G.; Schweizer, Barbara; Zamoiski, Rachel B.; McMahon, Francis J.; Nurnberger, John I., Jr.; Rice, John P.; Scheftner, William; Coryell, William; Berrettini, Wade H.; Kelsoe, John R.; Byerley, William; Gershon, Elliot S.; DePaulo, J. Raymond, Jr.; Potash, James B.; Medicine, School of MedicineOBJECTIVES: We sought to determine if postpartum mood symptoms and depressive episodes exhibit familial aggregation in bipolar I pedigrees. METHODS: A total of 1,130 women were interviewed with the Diagnostic Interview for Genetic Studies as part of the National Institute of Mental Health (NIMH) Genetics Initiative Bipolar Disorder Collaborative Study and were asked whether they had ever experienced mood symptoms within four weeks postpartum. Women were also asked whether either of two major depressive episodes described in detail occurred postpartum. We examined the odds of postpartum mood symptoms in female siblings, who had previously been pregnant and had a diagnosis of bipolar I, bipolar II, or schizoaffective (bipolar type) disorders (n = 303), given one or more relatives with postpartum mood symptoms. RESULTS: The odds ratio for familial aggregation of postpartum mood symptoms was 2.31 (p = 0.011) in an Any Mood Symptoms analysis (n = 304) and increased to 2.71 (p = 0.005) when manic symptoms were excluded, though this was not significantly different from the Any Mood Symptoms analysis. We also examined familial aggregation of postpartum major depressive episodes; however, the number of subjects was small. CONCLUSIONS: Limitations of the study include the retrospective interview, the fact that the data were collected for other purposes and the inability to control for such factors as medication use. Taken together with previous studies, these data provide support for the hypothesis that there may be a genetic basis for the trait of postpartum mood symptoms generally and postpartum depressive symptoms in particular in women with bipolar disorder. Genetic linkage and association studies incorporating this trait are warranted.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 MedicineBipolar 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.Item Genome-wide parametric linkage analyses of 644 bipolar pedigrees suggest susceptibility loci at chromosomes 16 and 20(Ovid Technologies (Wolters Kluwer) - Lippincott Williams & Wilkins, 2008-08) Ross, Jessica; Berrettini, Wade; Coryell, William; Gershon, Elliot S.; Badner, Judith A.; Kelsoe, John R.; McInnis, Melvin G.; McMahon, Francis J.; Murphy, Dennis L.; Nurnberger, John I.; Foroud, Tatiana; Rice, John P.; Scheftner, William B.; Zandi, Peter; Edenberg, Howard; Byerley, William; Department of Psychiatry, IU School of MedicineOBJECTIVE: Our aim is to map chromosomal regions that harbor loci that increase susceptibility to bipolar disorder. METHODS: We analyzed 644 bipolar families ascertained by the National Institute of Mental Health Human Genetics Initiative for bipolar disorder. The families have been genotyped with microsatellite loci spaced every approximately 10 cM or less across the genome. Earlier analyses of these pedigrees have been limited to nonparametric (model-free) methods and thus, information from unaffected subjects with genotypes was not considered. In this study, we used parametric analyses assuming dominant and recessive transmission and specifying a maximum penetrance of 70%, so that information from unaffecteds could be weighed in the linkage analyses. As in previous linkage analyses of these pedigrees, we analyzed three diagnostic categories: model 1 included only bipolar I and schizoaffective, bipolar cases (1565 patients of whom approximately 4% were schizoaffective, bipolar); model 2 included all individuals in model 1 plus bipolar II patients (1764 total individuals); and model 3 included all individuals in model 2 with the addition of patients with recurrent major depressive disorder (2046 total persons). RESULTS: Assuming dominant inheritance the highest genome-wide pair-wise logarithm of the odds (LOD) score was 3.2 with D16S749 using model 2 patients. Multipoint analyses of this region yielded a maximum LOD score of 4.91. Under recessive transmission a number of chromosome 20 markers were positive and multipoint analyses of the area gave a maximum LOD of 3.0 with model 2 cases. CONCLUSION: The chromosome 16p and 20 regions have been implicated by some studies and the data reported herein provide additional suggestive evidence of bipolar susceptibility genes in these regions.Item A large-scale genome-wide association study meta-analysis of cannabis use disorder(Elsevier, 2020-12) Johnson, Emma C.; Demontis, Ditte; Thorgeirsson, Thorgeir E.; Walters, Raymond K.; Polimanti, Renato; Hatoum, Alexander S.; Sanchez-Roige, Sandra; Paul, Sarah E.; Wendt, Frank R.; Clarke, Toni-Kim; Lai, Dongbing; Reginsson, Gunnar W.; Zhou, Hang; He, June; Baranger, David A.A.; Gudbjartsson, Daniel F.; Wedow, Robbee; Adkins, Daniel E.; Adkins, Amy E.; Alexander, Jeffry; Bacanu, Silviu-Alin; Bigdeli, Tim B.; Boden, Joseph; Brown, Sandra A.; Bucholz, Kathleen K.; Bybjerg-Grauholm, Jonas; Corley, Robin P.; Degenhardt, Louisa; Dick, Danielle M.; Domingue, Benjamin W.; Fox, Louis; Goate, Alison M.; Gordon, Scott D.; Hack, Laura M.; Hancock, Dana B.; Hartz, Sarah M.; Hickie, Ian B.; Hougaard, David M.; Krauter, Kenneth; Lind, Penelope A.; McClintick, Jeanette N.; McQueen, Matthew B.; Meyers, Jacquelyn L.; Montgomery, Grant W.; Mors, Ole; Mortensen, Preben B.; Nordentoft, Merete; Pearson, John F.; Peterson, Roseann E.; Reynolds, Maureen D.; Rice, John P.; Runarsdottir, Valgerdur; Saccone, Nancy L.; Sherva, Richard; Silberg, Judy L.; Tarter, Ralph E.; Tyrfingsson, Thorarinn; Wall, Tamara L.; Webb, Bradley T.; Werge, Thomas; Wetherill, Leah; Wright, Margaret J.; Zellers, Stephanie; Adams, Mark J.; Bierut, Laura J.; Boardman, Jason D.; Copeland, William E.; Farrer, Lindsay A.; Foroud, Tatiana M.; Gillespie, Nathan A.; Grucza, Richard A.; Mullan Harris, Kathleen; Heath, Andrew C.; Hesselbrock, Victor; Hewitt, John K.; Hopfer, Christian J.; Horwood, John; Iacono, William G.; Johnson, Eric O.; Kendler, Kenneth S.; Kennedy, Martin A.; Kranzler, Henry R.; Madden, Pamela A.F.; Maes, Hermine H.; Maher, Brion S.; Martin, Nicholas G.; McGue, Matthew; McIntosh, Andrew M.; Medland, Sarah E.; Nelson, Elliot C.; Porjesz, Bernice; Riley, Brien P.; Stallings, Michael C.; Vanyukov, Michael M.; Vrieze, Scott; Davis, Lea K.; Bogdan, Ryan; Gelernter, Joel; Edenberg, Howard J.; Stefansson, Kari; Børglum, Anders D.; Agrawal, Arpana; Medical and Molecular Genetics, School of MedicineBackground: Variation in liability to cannabis use disorder has a strong genetic component (estimated twin and family heritability about 50-70%) and is associated with negative outcomes, including increased risk of psychopathology. The aim of the study was to conduct a large genome-wide association study (GWAS) to identify novel genetic variants associated with cannabis use disorder. Methods: To conduct this GWAS meta-analysis of cannabis use disorder and identify associations with genetic loci, we used samples from the Psychiatric Genomics Consortium Substance Use Disorders working group, iPSYCH, and deCODE (20 916 case samples, 363 116 control samples in total), contrasting cannabis use disorder cases with controls. To examine the genetic overlap between cannabis use disorder and 22 traits of interest (chosen because of previously published phenotypic correlations [eg, psychiatric disorders] or hypothesised associations [eg, chronotype] with cannabis use disorder), we used linkage disequilibrium score regression to calculate genetic correlations. Findings: We identified two genome-wide significant loci: a novel chromosome 7 locus (FOXP2, lead single-nucleotide polymorphism [SNP] rs7783012; odds ratio [OR] 1·11, 95% CI 1·07-1·15, p=1·84 × 10-9) and the previously identified chromosome 8 locus (near CHRNA2 and EPHX2, lead SNP rs4732724; OR 0·89, 95% CI 0·86-0·93, p=6·46 × 10-9). Cannabis use disorder and cannabis use were genetically correlated (rg 0·50, p=1·50 × 10-21), but they showed significantly different genetic correlations with 12 of the 22 traits we tested, suggesting at least partially different genetic underpinnings of cannabis use and cannabis use disorder. Cannabis use disorder was positively genetically correlated with other psychopathology, including ADHD, major depression, and schizophrenia. Interpretation: These findings support the theory that cannabis use disorder has shared genetic liability with other psychopathology, and there is a distinction between genetic liability to cannabis use and cannabis use disorder.Item A New Statistic to Evaluate Imputation Reliability(Public Library of Science, 2010-03-15) Lin, Peng; Hartz, Sarah M.; Zhang, Zhehao; Saccone, Scott F.; Wang, Jia; Tischfield, Jay A.; Edenberg, Howard J.; Kramer, John R.; Goate, Alison M.; Bierut, Laura J.; Rice, John P.; COGA Collaborators COGEND Collaborators, GENEVA; Biochemistry and Molecular Biology, School of MedicineBackground As the amount of data from genome wide association studies grows dramatically, many interesting scientific questions require imputation to combine or expand datasets. However, there are two situations for which imputation has been problematic: (1) polymorphisms with low minor allele frequency (MAF), and (2) datasets where subjects are genotyped on different platforms. Traditional measures of imputation cannot effectively address these problems. Methodology/Principal Findings We introduce a new statistic, the imputation quality score (IQS). In order to differentiate between well-imputed and poorly-imputed single nucleotide polymorphisms (SNPs), IQS adjusts the concordance between imputed and genotyped SNPs for chance. We first evaluated IQS in relation to minor allele frequency. Using a sample of subjects genotyped on the Illumina 1 M array, we extracted those SNPs that were also on the Illumina 550 K array and imputed them to the full set of the 1 M SNPs. As expected, the average IQS value drops dramatically with a decrease in minor allele frequency, indicating that IQS appropriately adjusts for minor allele frequency. We then evaluated whether IQS can filter poorly-imputed SNPs in situations where cases and controls are genotyped on different platforms. Randomly dividing the data into “cases” and “controls”, we extracted the Illumina 550 K SNPs from the cases and imputed the remaining Illumina 1 M SNPs. The initial Q-Q plot for the test of association between cases and controls was grossly distorted (λ = 1.15) and had 4016 false positives, reflecting imputation error. After filtering out SNPs with IQS<0.9, the Q-Q plot was acceptable and there were no longer false positives. We then evaluated the robustness of IQS computed independently on the two halves of the data. In both European Americans and African Americans the correlation was >0.99 demonstrating that a database of IQS values from common imputations could be used as an effective filter to combine data genotyped on different platforms. Conclusions/Significance IQS effectively differentiates well-imputed and poorly-imputed SNPs. It is particularly useful for SNPs with low minor allele frequency and when datasets are genotyped on different platforms.