Browsing by Author "Robinson, Elise B."

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    Principled distillation of UK Biobank phenotype data reveals underlying structure in human variation
    (Springer Nature, 2024) Carey, Caitlin E.; Shafee, Rebecca; Wedow, Robbee; Elliott, Amanda; Palmer, Duncan S.; Compitello, John; Kanai, Masahiro; Abbott, Liam; Schultz, Patrick; Karczewski, Konrad J.; Bryant, Samuel C.; Cusick, Caroline M.; Churchhouse, Claire; Howrigan, Daniel P.; King, Daniel; Smith, George Davey; Neale, Benjamin M.; Walters, Raymond K.; Robinson, Elise B.; Medical and Molecular Genetics, School of Medicine
    Data within biobanks capture broad yet detailed indices of human variation, but biobank-wide insights can be difficult to extract due to complexity and scale. Here, using large-scale factor analysis, we distill hundreds of variables (diagnoses, assessments and survey items) into 35 latent constructs, using data from unrelated individuals with predominantly estimated European genetic ancestry in UK Biobank. These factors recapitulate known disease classifications, disentangle elements of socioeconomic status, highlight the relevance of psychiatric constructs to health and improve measurement of pro-health behaviours. We go on to demonstrate the power of this approach to clarify genetic signal, enhance discovery and identify associations between underlying phenotypic structure and health outcomes. In building a deeper understanding of ways in which constructs such as socioeconomic status, trauma, or physical activity are structured in the dataset, we emphasize the importance of considering the interwoven nature of the human phenome when evaluating public health patterns.
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    The Landscape of Shared and Divergent Genetic Influences across 14 Psychiatric Disorders
    (medRxiv, 2025-01-15) Grotzinger, Andrew D.; Werme, Josefin; Peyrot, Wouter J.; Frei, Oleksandr; de Leeuw, Christiaan; Bicks, Lucy K.; Guo, Qiuyu; Margolis, Michael P.; Coombes, Brandon J.; Batzler, Anthony; Pazdernik, Vanessa; Biernacka, Joanna M.; Andreassen, Ole A.; Anttila, Verneri; Børglum, Anders D.; Cai, Na; Demontis, Ditte; Edenberg, Howard J.; Faraone, Stephen V.; Franke, Barbara; Gandal, Michael J.; Gelernter, Joel; Hettema, John M.; Jonas, Katherine G.; Knowles, James A.; Koenen, Karestan C.; Maihofer, Adam X.; Mallard, Travis T.; Mattheisen, Manuel; Mitchell, Karen S.; Neale, Benjamin M.; Nievergelt, Caroline M.; Nurnberger, John I.; O'Connell, Kevin S.; Robinson, Elise B.; Sanchez-Roige, Sandra S.; Santangelo, Susan L.; Stefansson, Hreinn; Stefansson, Kari; Stein, Murray B.; Strom, Nora I.; Thornton, Laura M.; Tucker-Drob, Elliot M.; Verhulst, Brad; Waldman, Irwin D.; Walters, G. Bragi; Wray, Naomi R.; Anxiety Disorders Working Group; Attention-Deficit/Hyperactivity Disorder (ADHD) Working Group; Autism Spectrum Disorders Working Group; Bipolar Disorder Working Group; Eating Disorders Working Group; Major Depressive Disorder Working Group; Nicotine Dependence GenOmics (iNDiGO) Consortium; Obsessive-Compulsive Disorder Working Group; Post-Traumatic Stress Disorder Working Group; Schizophrenia Working Group; Substance Use Disorders Working Group; Tourette Syndrome Working Group; Lee, Phil H.; Kendler, Kenneth S.; Smoller, Jordan W.; Biochemistry and Molecular Biology, School of Medicine
    Psychiatric disorders display high levels of comorbidity and genetic overlap 1,2. Genomic methods have shown that even for schizophrenia and bipolar disorder, two disorders long-thought to be etiologically distinct 3, the majority of genetic signal is shared 4. Furthermore, recent cross-disorder analyses have uncovered over a hundred pleiotropic loci shared across eight disorders 5. However, the full scope of shared and disorder-specific genetic basis of psychopathology remains largely uncharted. Here, we address this gap by triangulating across a suite of cutting-edge statistical genetic and functional genomic analyses applied to 14 childhood- and adult-onset psychiatric disorders (1,056,201 cases). Our analyses identify and characterize five underlying genomic factors 6 that explain the majority of the genetic variance of the individual disorders (~66% on average) and are associated with 268 pleiotropic loci. We observed particularly high levels of polygenic overlap 7 and local genetic correlation 8 and very few disorder-specific loci 9 for two factors defined by: (i) schizophrenia and bipolar disorder ("SB factor"), and by (ii) major depression, PTSD, and anxiety ("internalizing factor"). At the functional level, we applied multiple methods 10-12 which demonstrated that the shared genetic signal across the SB factor was substantially enriched in genes expressed in excitatory neurons, whereas the internalizing factor was associated with oligodendrocyte biology. By comparison, the genetic signal shared across all 14 disorders was enriched for broad biological processes (e.g., transcriptional regulation). These results indicate increasing differentiation of biological function at different levels of shared cross-disorder risk, from quite general vulnerability to more specific pathways associated with subsets of disorders. These observations may inform a more neurobiologically valid psychiatric nosology and implicate novel targets for therapeutic developments designed to treat commonly occurring comorbid presentations.