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1.	Evangelou, Evangelos, et al. (author) Genetic analysis of over 1 million people identifies 535 new loci associated with blood pressure traits. 2018 In: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 50:10, s. 1412-1425 Journal article (peer-reviewed)abstract High blood pressure is a highly heritable and modifiable risk factor for cardiovascular disease. We report the largest genetic association study of blood pressure traits (systolic, diastolic and pulse pressure) to date in over 1 million people of European ancestry. We identify 535 novel blood pressure loci that not only offer new biological insights into blood pressure regulation but also highlight shared genetic architecture between blood pressure and lifestyle exposures. Our findings identify new biological pathways for blood pressure regulation with potential for improved cardiovascular disease prevention in the future.
2.	Ried, Janina S., et al. (author) A principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shape 2016 In: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 7 Journal article (peer-reviewed)abstract Large consortia have revealed hundreds of genetic loci associated with anthropometric traits, one trait at a time. We examined whether genetic variants affect body shape as a composite phenotype that is represented by a combination of anthropometric traits. We developed an approach that calculates averaged PCs (AvPCs) representing body shape derived from six anthropometric traits (body mass index, height, weight, waist and hip circumference, waist-to-hip ratio). The first four AvPCs explain >99% of the variability, are heritable, and associate with cardiometabolic outcomes. We performed genome-wide association analyses for each body shape composite phenotype across 65 studies and meta-analysed summary statistics. We identify six novel loci: LEMD2 and CD47 for AvPC1, RPS6KA5/C14orf159 and GANAB for AvPC3, and ARL15 and ANP32 for AvPC4. Our findings highlight the value of using multiple traits to define complex phenotypes for discovery, which are not captured by single-trait analyses, and may shed light onto new pathways.

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Type of publication: journal article (2)

Type of content: peer-reviewed (2)

Author/Editor: Salomaa, Veikko (2); Jula, Antti (2); Perola, Markus (2); Raitakari, Olli T (2); Campbell, Harry (2); Rudan, Igor (2); show more...; Strachan, David P (2); Wareham, Nicholas J. (2); Laakso, Markku (2); Ridker, Paul M. (2); Chasman, Daniel I. (2); van Duijn, Cornelia ... (2); Rose, Lynda M (2); Langenberg, Claudia (2); Boehnke, Michael (2); Hamsten, Anders (2); Scott, Robert A (2); Havulinna, Aki S. (2); Kähönen, Mika (2); Lehtimäki, Terho (2); Tuomilehto, Jaakko (2); Verweij, Niek (2); Koskinen, Seppo (2); Mangino, Massimo (2); Willemsen, Gonneke (2); Oostra, Ben A. (2); Gieger, Christian (2); Peters, Annette (2); Boomsma, Dorret I. (2); Jarvelin, Marjo-Riit ... (2); Mahajan, Anubha (2); Luan, Jian'an (2); Metspalu, Andres (2); Farrall, Martin (2); Hicks, Andrew A. (2); Pramstaller, Peter P ... (2); Wright, Alan F. (2); Wilson, James F. (2); Jousilahti, Pekka (2); Zhao, Jing Hua (2); Huffman, Jennifer E (2); Loos, Ruth J F (2); Hofman, Albert (2); Kolcic, Ivana (2); Uitterlinden, André ... (2); Psaty, Bruce M (2); Vitart, Veronique (2); Wild, Sarah H (2); Hayward, Caroline (2); Zeggini, Eleftheria (2); show less...

University: Lund University (2); Karolinska Institutet (2); University of Gothenburg (1); Uppsala University (1); Stockholm University (1)

Language: English (2)

Research subject (UKÄ/SCB): Medical and Health Sciences (2); Natural sciences (1)

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