123987 20240319081028.0 doi 10.1186/s13059-022-02837-1 sideral 132581 ART-2022-132581 eng Kanoni, S. Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis 2022 Access copy available to the general public Unrestricted Background: Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results: To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3-5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions: Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk. info:eu-repo/grantAgreement/EC/FP7/608765/EU/WILLIAM HARVEY INTERNATIONAL TRANSLATIONAL RESEARCH ACADEMY/WHRI-ACADEMY info:eu-repo/grantAgreement/EC/H2020/786833/EU/GENetics and the Electrocardiogram for predicting Scd rISk/GENESIS This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 786833-GENESIS info:eu-repo/grantAgreement/ES/ISCIII/PI17-00142 info:eu-repo/semantics/openAccess by http://creativecommons.org/licenses/by/3.0/es/ 12.3 2022 GENETICS & HEREDITY 5 / 171 = 0.029 2022 Q1 T1 BIOTECHNOLOGY & APPLIED MICROBIOLOGY 9 / 158 = 0.057 2022 Q1 T1 9.249 2022 Cell Biology 2022 Q1 Genetics 2022 Q1 Ecology, Evolution, Behavior and Systematics 2022 Q1 25.5 2022 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Graham, S. E. Wang, Y. Surakka, I. Ramdas, S. Zhu, X. Clarke, S. L. Bhatti, K. F. Vedantam, S. Winkler, T. W. Locke, A. E. Marouli, E. Zajac, G. J. M. Wu, K.H. H. Ntalla, I. Hui, Q. Klarin, D. Hiliard, A.T. Wang, Z. Xue, Ch. Thorleidson, G. Helgadottir, A. Gudbjartsson, D. F. Holm, H. Olafsson, I. Hwang, M. Y.: Han, S. Akiyama, M. Sakue, S. Terao, S. Kanai, M. Zhou, W. Brumpton, B. M. Rasheed, H. Havulinna, A. S. Veturi, Y. Ramírez, J. Universidad de Zaragoza (orcid)0000-0003-4130-5866 5008 800 Universidad de Zaragoza Dpto. Ingeniería Electrón.Com. Área Teoría Señal y Comunicac. 23 (2022), 268[42 pp.] Genome Biol. Genome biology 1474-7596 2235978 http://zaguan.unizar.es/record/123987/files/texto_completo.pdf Versión publicada 2338518 http://zaguan.unizar.es/record/123987/files/texto_completo.jpg?subformat=icon icon Versión publicada oai:zaguan.unizar.es:123987 articulos driver 2024-03-18-16:57:10 ARTICLE