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Browsing by Subject "Genomic structural equation modeling"
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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 The relationship between cannabis and schizophrenia: a genetically informed perspective(Wiley, 2021) Johnson, Emma C.; Hatoum, Alexander S.; Deak, Joseph D.; Polimanti, Renato; Murray, Robin M.; Edenberg, Howard J.; Gelernter, Joel; Di Forti, Marta; Agrawal, Arpana; Medical and Molecular Genetics, School of MedicineBackground and aims: While epidemiological studies support a role for heavy, high-potency cannabis use on first-episode psychosis, genetic models of causation suggest reverse causal effects of schizophrenia on cannabis use liability. We estimated the genetic relationship between cannabis use disorder (CUD) and schizophrenia (SCZ) and tested whether liability for CUD is causally associated with increased liability to SCZ while adjusting for tobacco smoking. Design: This study used summary statistics from published genome-wide association studies (GWAS). We used genomic structural equation modeling, latent causal variable analysis, and multivariable Mendelian randomization to examine genetic relationships between CUD, cannabis ever-use, ever-smoked tobacco regularly, nicotine dependence and SCZ, and to test for a causal relationship between liability to CUD and liability to SCZ. Setting: Genome-wide association studies were published previously as part of international consortia. Participants: Sample sizes of the GWAS summary statistics used in this study ranged from 161 405 to 357 806 individuals of European ancestry. Measurements: Genome-wide summary statistics for CUD and SCZ were the primary measurements, while summary statistics for cannabis ever-use, ever-smoked tobacco regularly and nicotine dependence were included as additional variables in the genomic structural equation models and the multivariable Mendelian randomization analyses. Findings: Genetic liability to CUD was significantly associated with SCZ [β = 0.29, 95% confidence interval (CI) = 0.11, 0.46, P = 0.001], even when accounting for cannabis ever-use, ever-smoked tobacco regularly and nicotine dependence as simultaneous predictors. We found mixed evidence of a causal relationship, with the latent causal variable analysis finding no evidence of causality (genetic causality proportion = -0.08, 95% CI = -0.40, 0.23, P = 0.87) but the multivariable Mendelian randomization analyses suggesting a significant, risk-increasing effect of CUD on liability to SCZ (β = 0.10, 95% CI = 0.02, 0.18, P = 0.02), accounting for the additional risk factors (cannabis ever-use, ever-smoked tobacco regularly and nicotine dependence). Conclusions: Genetic liability for cannabis use disorder appears to be robustly associated with schizophrenia, above and beyond tobacco smoking and cannabis ever-use, with mixed evidence to support a causal relationship between cannabis use disorder and schizophrenia.