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Browsing by Author "Davis, Lea K."
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Item Cross-ancestry genetic investigation of schizophrenia, cannabis use disorder, and tobacco smoking(medRxiv, 2024-01-18) Johnson, Emma C.; Austin-Zimmerman, Isabelle; Thorpe, Hayley H. A.; Levey, Daniel F.; Baranger, David A. A.; Colbert, Sarah M. C.; Demontis, Ditte; Khokhar, Jibran Y.; Davis, Lea K.; Edenberg, Howard J.; Di Forti, Marta; Sanchez-Roige, Sandra; Gelernter, Joel; Agrawal, Arpana; Biochemistry and Molecular Biology, School of MedicineIndividuals with schizophrenia frequently experience co-occurring substance use, including tobacco smoking and heavy cannabis use, and substance use disorders. There is interest in understanding the extent to which these relationships are causal, and to what extent shared genetic factors play a role. We explored the relationships between schizophrenia (Scz), cannabis use disorder (CanUD), and ever-regular tobacco smoking (Smk) using the largest available genome-wide studies of these phenotypes in individuals of African and European ancestries. All three phenotypes were positively genetically correlated (rgs = 0.17 - 0.62). Causal inference analyses suggested the presence of horizontal pleiotropy, but evidence for bidirectional causal relationships was also found between all three phenotypes even after correcting for horizontal pleiotropy. We identified 439 pleiotropic loci in the European ancestry data, 150 of which were novel (i.e., not genome-wide significant in the original studies). Of these pleiotropic loci, 202 had lead variants which showed convergent effects (i.e., same direction of effect) on Scz, CanUD, and Smk. Genetic variants convergent across all three phenotypes showed strong genetic correlations with risk-taking, executive function, and several mental health conditions. Our results suggest that both horizontal pleiotropy and causal mechanisms may play a role in the relationship between CanUD, Smk, and Scz, but longitudinal, prospective studies are needed to confirm a causal relationship.Item Examining Sex-Differentiated Genetic Effects Across Neuropsychiatric and Behavioral Traits(Elsevier, 2021-06-15) Martin, Joanna; Khramtsova, Ekaterina A.; Goleva, Slavina B.; Blokland, Gabriëlla A.M.; Traglia, Michela; Walters, Raymond K.; Hübel, Christopher; Coleman, Jonathan R.I.; Breen, Gerome; Børglum, Anders D.; Demontis, Ditte; Grove, Jakob; Werge, Thomas; Bralten, Janita; Bulik, Cynthia M.; Lee, Phil H.; Mathews, Carol A.; Peterson, Roseann E.; Winham, Stacey J.; Wray, Naomi; Edenberg, Howard J.; Guo, Wei; Yao, Yin; Neale, Benjamin M.; Faraone, Stephen V.; Petryshen, Tracey L.; Weiss, Lauren A.; Duncan, Laramie E.; Goldstein, Jill M.; Smoller, Jordan W.; Stranger, Barbara E.; Davis, Lea K.; Biochemistry and Molecular Biology, School of MedicineBackground: The origin of sex differences in prevalence and presentation of neuropsychiatric and behavioral traits is largely unknown. Given established genetic contributions and correlations, we tested for a sex-differentiated genetic architecture within and between traits. Methods: Using European ancestry genome-wide association summary statistics for 20 neuropsychiatric and behavioral traits, we tested for sex differences in single nucleotide polymorphism (SNP)-based heritability and genetic correlation (rg < 1). For each trait, we computed per-SNP z scores from sex-stratified regression coefficients and identified genes with sex-differentiated effects using a gene-based approach. We calculated correlation coefficients between z scores to test for shared sex-differentiated effects. Finally, we tested for sex differences in across-trait genetic correlations. Results: We observed no consistent sex differences in SNP-based heritability. Between-sex, within-trait genetic correlations were high, although <1 for educational attainment and risk-taking behavior. We identified 4 genes with significant sex-differentiated effects across 3 traits. Several trait pairs shared sex-differentiated effects. The top genes with sex-differentiated effects were enriched for multiple gene sets, including neuron- and synapse-related sets. Most between-trait genetic correlation estimates were not significantly different between sexes, with exceptions (educational attainment and risk-taking behavior). Conclusions: Sex differences in the common autosomal genetic architecture of neuropsychiatric and behavioral phenotypes are small and polygenic and unlikely to fully account for observed sex-differentiated attributes. Larger sample sizes are needed to identify sex-differentiated effects for most traits. For well-powered studies, we identified genes with sex-differentiated effects that were enriched for neuron-related and other biological functions. This work motivates further investigation of genetic and environmental influences on sex differences.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 MedicineProblematic 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.Item Item-Level Genome-Wide Association Study of the Alcohol Use Disorders Identification Test in Three Population-Based Cohorts(American Psychiatric Association, 2022) Mallard, Travis T.; Savage, Jeanne E.; Johnson, Emma C.; Huang, Yuye; Edwards, Alexis C.; Hottenga, Jouke J.; Grotzinger, Andrew D.; Gustavson, Daniel E.; Jennings, Mariela V.; Anokhin, Andrey; Dick, Danielle M.; Edenberg, Howard J.; Kramer, John R.; Lai, Dongbing; Meyers, Jacquelyn L.; Pandey, Ashwini K.; Harden, Kathryn Paige; Nivard, Michel G.; de Geus, Eco J. C.; Boomsma, Dorret I.; Agrawal, Arpana; Davis, Lea K.; Clarke, Toni-Kim; Palmer, Abraham A.; Sanchez-Roige, Sandra; Biochemistry and Molecular Biology, School of MedicineObjective: Genome-wide association studies (GWASs) of the Alcohol Use Disorders Identification Test (AUDIT), a 10-item screen for alcohol use disorder (AUD), have elucidated novel loci for alcohol consumption and misuse. However, these studies also revealed that GWASs can be influenced by numerous biases (e.g., measurement error, selection bias), which may have led to inconsistent genetic correlations between alcohol involvement and AUD, as well as paradoxically negative genetic correlations between alcohol involvement and psychiatric disorders and/or medical conditions. The authors used genomic structural equation modeling to elucidate the genetics of alcohol consumption and problematic consequences of alcohol use as measured by AUDIT. Methods: To explore these unexpected differences in genetic correlations, the authors conducted the first item-level and the largest GWAS of AUDIT items (N=160,824) and applied a multivariate framework to mitigate previous biases. Results: The authors identified novel patterns of similarity (and dissimilarity) among the AUDIT items and found evidence of a correlated two-factor structure at the genetic level ("consumption" and "problems," rg=0.80). Moreover, by applying empirically derived weights to each of the AUDIT items, the authors constructed an aggregate measure of alcohol consumption that was strongly associated with alcohol dependence (rg=0.67), moderately associated with several other psychiatric disorders, and no longer positively associated with health and positive socioeconomic outcomes. Lastly, by conducting polygenic analyses in three independent cohorts that differed in their ascertainment and prevalence of AUD, the authors identified novel genetic associations between alcohol consumption, alcohol misuse, and health. Conclusions: This work further emphasizes the value of AUDIT for both clinical and genetic studies of AUD and the importance of using multivariate methods to study genetic associations that are more closely related to AUD.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 Multi-ancestry study of the genetics of problematic alcohol use in over 1 million individuals(Springer Nature, 2023) Zhou, Hang; Kember, Rachel L.; Deak, Joseph D.; Xu, Heng; Toikumo, Sylvanus; Yuan, Kai; Lind, Penelope A.; Farajzadeh, Leila; Wang, Lu; Hatoum, Alexander S.; Johnson, Jessica; Lee, Hyunjoon; Mallard, Travis T.; Xu, Jiayi; Johnston, Keira J. A.; Johnson, Emma C.; Galimberti, Marco; Dao, Cecilia; Levey, Daniel F.; Overstreet, Cassie; Byrne, Enda M.; Gillespie, Nathan A.; Gordon, Scott; Hickie, Ian B.; Whitfield, John B.; Xu, Ke; Zhao, Hongyu; Huckins, Laura M.; Davis, Lea K.; Sanchez-Roige, Sandra; Madden, Pamela A. F.; Heath, Andrew C.; Medland, Sarah E.; Martin, Nicholas G.; Ge, Tian; Smoller, Jordan W.; Hougaard, David M.; Børglum, Anders D.; Demontis, Ditte; Krystal, John H.; Gaziano, J. Michael; Edenberg, Howard J.; Agrawal, Arpana; Million Veteran Program; Justice, Amy C.; Stein, Murray B.; Kranzler, Henry R.; Gelernter, Joel; Biochemistry and Molecular Biology, School of MedicineProblematic alcohol use (PAU), a trait that combines alcohol use disorder and alcohol-related problems assessed with a questionnaire, is a leading cause of death and morbidity worldwide. Here we conducted a large cross-ancestry meta-analysis of PAU in 1,079,947 individuals (European, N = 903,147; African, N = 122,571; Latin American, N = 38,962; East Asian, N = 13,551; and South Asian, N = 1,716 ancestries). We observed a high degree of cross-ancestral similarity in the genetic architecture of PAU and identified 110 independent risk variants in within- and cross-ancestry analyses. Cross-ancestry fine mapping improved the identification of likely causal variants. Prioritizing genes through gene expression and chromatin interaction in brain tissues identified multiple genes associated with PAU. We identified existing medications for potential pharmacological studies by a computational drug repurposing analysis. Cross-ancestry polygenic risk scores showed better performance of association in independent samples than single-ancestry polygenic risk scores. Genetic correlations between PAU and other traits were observed in multiple ancestries, with other substance use traits having the highest correlations. This study advances our knowledge of the genetic etiology of PAU, and these findings may bring possible clinical applicability of genetics insights-together with neuroscience, biology and data science-closer.Item Multivariate genome-wide association meta-analysis of over 1 million subjects identifies loci underlying multiple substance use disorders(Springer Nature, 2023) Hatoum, Alexander S.; Colbert, Sarah M. C.; Johnson, Emma C.; Huggett, Spencer B.; Deak, Joseph D.; Pathak, Gita; Jennings, Mariela V.; Paul, Sarah E.; Karcher, Nicole R.; Hansen, Isabella; Baranger, David A. A.; Edwards, Alexis; Grotzinger, Andrew; Substance Use Disorder Working Group of the Psychiatric Genomics Consortium; Tucker-Drob, Elliot M.; Kranzler, Henry R.; Davis, Lea K.; Sanchez-Roige, Sandra; Polimanti, Renato; Gelernter, Joel; Edenberg, Howard J.; Bogdan, Ryan; Agrawal, Arpana; Medical and Molecular Genetics, School of MedicineGenetic liability to substance use disorders can be parsed into loci that confer general or substance-specific addiction risk. We report a multivariate genome-wide association meta-analysis that disaggregates general and substance-specific loci for published summary statistics of problematic alcohol use, problematic tobacco use, cannabis use disorder, and opioid use disorder in a sample of 1,025,550 individuals of European descent and 92,630 individuals of African descent. Nineteen independent SNPs were genome-wide significant (P < 5e-8) for the general addiction risk factor (addiction-rf), which showed high polygenicity. Across ancestries, PDE4B was significant (among other genes), suggesting dopamine regulation as a cross-substance vulnerability. An addiction-rf polygenic risk score was associated with substance use disorders, psychopathologies, somatic conditions, and environments associated with the onset of addictions. Substance-specific loci (9 for alcohol, 32 for tobacco, 5 for cannabis, 1 for opioids) included metabolic and receptor genes. These findings provide insight into genetic risk loci for substance use disorders that could be leveraged as treatment targets