Browsing by Author "Karczewski, Konrad J."

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    A cross-disorder dosage sensitivity map of the human genome
    (Elsevier, 2022) Collins, Ryan L.; Glessner, Joseph T.; Porcu, Eleonora; Lepamets, Maarja; Brandon, Rhonda; Lauricella, Christopher; Han, Lide; Morley, Theodore; Niestroj, Lisa-Marie; Ulirsch, Jacob; Everett, Selin; Howrigan, Daniel P.; Boone, Philip M.; Fu, Jack; Karczewski, Konrad J.; Kellaris, Georgios; Lowther, Chelsea; Lucente, Diane; Mohajeri, Kiana; Nõukas, Margit; Nuttle, Xander; Samocha, Kaitlin E.; Trinh, Mi; Ullah, Farid; Võsa, Urmo; Epi25 Consortium; Estonian Biobank Research Team; Hurles, Matthew E.; Aradhya, Swaroop; Davis, Erica E.; Finucane, Hilary; Gusella, James F.; Janze, Aura; Katsanis, Nicholas; Matyakhina, Ludmila; Neale, Benjamin M.; Sanders, David; Warren, Stephanie; Hodge, Jennelle C.; Lal, Dennis; Ruderfer, Douglas M.; Meck, Jeanne; Mägi, Reedik; Esko, Tõnu; Reymond, Alexandre; Kutalik, Zoltán; Hakonarson, Hakon; Sunyaev, Shamil; Brand, Harrison; Talkowski, Michael E.; Medical and Molecular Genetics, School of Medicine
    Rare copy-number variants (rCNVs) include deletions and duplications that occur infrequently in the global human population and can confer substantial risk for disease. In this study, we aimed to quantify the properties of haploinsufficiency (i.e., deletion intolerance) and triplosensitivity (i.e., duplication intolerance) throughout the human genome. We harmonized and meta-analyzed rCNVs from nearly one million individuals to construct a genome-wide catalog of dosage sensitivity across 54 disorders, which defined 163 dosage sensitive segments associated with at least one disorder. These segments were typically gene dense and often harbored dominant dosage sensitive driver genes, which we were able to prioritize using statistical fine-mapping. Finally, we designed an ensemble machine-learning model to predict probabilities of dosage sensitivity (pHaplo & pTriplo) for all autosomal genes, which identified 2,987 haploinsufficient and 1,559 triplosensitive genes, including 648 that were uniquely triplosensitive. This dosage sensitivity resource will provide broad utility for human disease research and clinical genetics.
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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.