Browsing by Author "Grotzinger, Andrew"

Now showing 1 - 4 of 4
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    Alcohol Use and Alcohol Use Disorder Differ in their Genetic Relationships with PTSD: A Genomic Structural Equation Modelling Approach
    (Elsevier, 2022) Bountress, Kaitlin E.; Brick, Leslie A.; Sheerin, Christina; Grotzinger, Andrew; Bustamante, Daniel; Hawn, Sage E.; Gillespie, Nathan; Kirkpatrick, Robert M.; Kranzler, Henry; Morey, Rajendra; Edenberg, Howard J.; Maihofer, Adam X.; Disner, Seth; Ashley-Koch, Allison; Peterson, Roseann; Lori, Adriana; Stein, Dan J.; Kimbrel, Nathan; Nievergelt, Caroline; Andreassen, Ole A.; Luykx, Jurjen; Javanbakht, Arash; Youssef, Nagy A.; Psychiatric Genomics Consortium Posttraumatic Stress Disorder Working Group; Amstadter, Ananda B.; Biochemistry and Molecular Biology, School of Medicine
    Purpose: Posttraumatic Stress Disorder (PTSD) is associated with increased alcohol use and alcohol use disorder (AUD), which are all moderately heritable. Studies suggest the genetic association between PTSD and alcohol use differs from that of PTSD and AUD, but further analysis is needed. Basic procedures: We used genomic Structural Equation Modeling (genomicSEM) to analyze summary statistics from large-scale genome-wide association studies (GWAS) of European Ancestry participants to investigate the genetic relationships between PTSD (both diagnosis and re-experiencing symptom severity) and a range of alcohol use and AUD phenotypes. Main findings: When we differentiated genetic factors for alcohol use and AUD we observed improved model fit relative to models with all alcohol-related indicators loading onto a single factor. The genetic correlations (rG) of PTSD were quite discrepant for the alcohol use and AUD factors. This was true when modeled as a three-correlated-factor model (PTSD-AUD rG:.36, p < .001; PTSD-alcohol use rG: -0.17, p < .001) and as a Bifactor model, in which the common and unique portions of alcohol phenotypes were pulled out into an AUD-specific factor (rG with PTSD:.40, p < .001), AU-specific factor (rG with PTSD: -0.57, p < .001), and a common alcohol factor (rG with PTSD:.16, NS). Principal conclusions: These results indicate the genetic architecture of alcohol use and AUD are differentially associated with PTSD. When the portions of variance unique to alcohol use and AUD are extracted, their genetic associations with PTSD vary substantially, suggesting different genetic architectures of alcohol phenotypes in people with PTSD.
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    Assessment and ascertainment in psychiatric molecular genetics: challenges and opportunities for cross-disorder research
    (Springer Nature, 2025) Cai, Na; Verhulst, Brad; Andreassen, Ole A.; Buitelaar, Jan; Edenberg, Howard J.; Hettema, John M.; Gandal, Michael; Grotzinger, Andrew; Jonas, Katherine; Lee, Phil; Mallard, Travis T.; Mattheisen, Manuel; Neale, Michael C.; Nurnberger, John I., Jr.; Peyrot, Wouter J.; Tucker-Drob, Elliot M.; Smoller, Jordan W.; Kendler, Kenneth S.; Biochemistry and Molecular Biology, School of Medicine
    Psychiatric disorders are highly comorbid, heritable, and genetically correlated [1-4]. The primary objective of cross-disorder psychiatric genetics research is to identify and characterize both the shared genetic factors that contribute to convergent disease etiologies and the unique genetic factors that distinguish between disorders [4, 5]. This information can illuminate the biological mechanisms underlying comorbid presentations of psychopathology, improve nosology and prediction of illness risk and trajectories, and aid the development of more effective and targeted interventions. In this review we discuss how estimates of comorbidity and identification of shared genetic loci between disorders can be influenced by how disorders are measured (phenotypic assessment) and the inclusion or exclusion criteria in individual genetic studies (sample ascertainment). Specifically, the depth of measurement, source of diagnosis, and time frame of disease trajectory have major implications for the clinical validity of the assessed phenotypes. Further, biases introduced in the ascertainment of both cases and controls can inflate or reduce estimates of genetic correlations. The impact of these design choices may have important implications for large meta-analyses of cohorts from diverse populations that use different forms of assessment and inclusion criteria, and subsequent cross-disorder analyses thereof. We review how assessment and ascertainment affect genetic findings in both univariate and multivariate analyses and conclude with recommendations for addressing them in future research.
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    Correction: Assessment and ascertainment in psychiatric molecular genetics: challenges and opportunities for cross-disorder research
    (Springer Nature, 2025) Cai, Na; Verhulst, Brad; Andreassen, Ole A.; Buitelaar, Jan; Edenberg, Howard J.; Hettema, John M.; Gandal, Michael; Grotzinger, Andrew; Jonas, Katherine; Lee, Phil; Mallard, Travis T.; Mattheisen, Manuel; Neale, Michael C.; Nurnberger, John I., Jr.; Peyrot, Wouter J.; Tucker-Drob, Elliot M.; Smoller, Jordan W.; Kendler, Kenneth S.; Biochemistry and Molecular Biology, School of Medicine
    Correction to: Molecular Psychiatry 10.1038/s41380-024-02878-x, published online 27 December 2024 In this article the author’s name Wouter J. Peyrot was incorrectly written as Wouter Peyrout. The original article has been corrected.
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    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 Medicine
    Genetic 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