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The Molecular Genetic Architecture of Self-Employment

Overview of attention for article published in PLOS ONE, April 2013
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Title
The Molecular Genetic Architecture of Self-Employment
Published in
PLOS ONE, April 2013
DOI 10.1371/journal.pone.0060542
Pubmed ID
Authors

Matthijs J. H. M. van der Loos, Cornelius A. Rietveld, Niina Eklund, Philipp D. Koellinger, Fernando Rivadeneira, Gonçalo R. Abecasis, Georgina A. Ankra-Badu, Sebastian E. Baumeister, Daniel J. Benjamin, Reiner Biffar, Stefan Blankenberg, Dorret I. Boomsma, David Cesarini, Francesco Cucca, Eco J. C. de Geus, George Dedoussis, Panos Deloukas, Maria Dimitriou, Guðny Eiriksdottir, Johan Eriksson, Christian Gieger, Vilmundur Gudnason, Birgit Höhne, Rolf Holle, Jouke-Jan Hottenga, Aaron Isaacs, Marjo-Riitta Järvelin, Magnus Johannesson, Marika Kaakinen, Mika Kähönen, Stavroula Kanoni, Maarit A. Laaksonen, Jari Lahti, Lenore J. Launer, Terho Lehtimäki, Marisa Loitfelder, Patrik K. E. Magnusson, Silvia Naitza, Ben A. Oostra, Markus Perola, Katja Petrovic, Lydia Quaye, Olli Raitakari, Samuli Ripatti, Paul Scheet, David Schlessinger, Carsten O. Schmidt, Helena Schmidt, Reinhold Schmidt, Andrea Senft, Albert V. Smith, Timothy D. Spector, Ida Surakka, Rauli Svento, Antonio Terracciano, Emmi Tikkanen, Cornelia M. van Duijn, Jorma Viikari, Henry Völzke, H. -Erich Wichmann, Philipp S. Wild, Sara M. Willems, Gonneke Willemsen, Frank J. A. van Rooij, Patrick J. F. Groenen, André G. Uitterlinden, Albert Hofman, A. Roy Thurik

Abstract

Economic variables such as income, education, and occupation are known to affect mortality and morbidity, such as cardiovascular disease, and have also been shown to be partly heritable. However, very little is known about which genes influence economic variables, although these genes may have both a direct and an indirect effect on health. We report results from the first large-scale collaboration that studies the molecular genetic architecture of an economic variable-entrepreneurship-that was operationalized using self-employment, a widely-available proxy. Our results suggest that common SNPs when considered jointly explain about half of the narrow-sense heritability of self-employment estimated in twin data (σ(g)(2)/σ(P)(2) = 25%, h(2) = 55%). However, a meta-analysis of genome-wide association studies across sixteen studies comprising 50,627 participants did not identify genome-wide significant SNPs. 58 SNPs with p<10(-5) were tested in a replication sample (n = 3,271), but none replicated. Furthermore, a gene-based test shows that none of the genes that were previously suggested in the literature to influence entrepreneurship reveal significant associations. Finally, SNP-based genetic scores that use results from the meta-analysis capture less than 0.2% of the variance in self-employment in an independent sample (p≥0.039). Our results are consistent with a highly polygenic molecular genetic architecture of self-employment, with many genetic variants of small effect. Although self-employment is a multi-faceted, heavily environmentally influenced, and biologically distal trait, our results are similar to those for other genetically complex and biologically more proximate outcomes, such as height, intelligence, personality, and several diseases.

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Geographical breakdown

Country Count As %
Germany 1 <1%
Finland 1 <1%
United Kingdom 1 <1%
United States 1 <1%
Luxembourg 1 <1%
Unknown 112 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 24 21%
Researcher 15 13%
Student > Bachelor 12 10%
Professor 10 9%
Other 8 7%
Other 28 24%
Unknown 20 17%
Readers by discipline Count As %
Psychology 14 12%
Agricultural and Biological Sciences 12 10%
Social Sciences 12 10%
Economics, Econometrics and Finance 11 9%
Biochemistry, Genetics and Molecular Biology 10 9%
Other 30 26%
Unknown 28 24%