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Meta-Analysis
. 2013 Apr 4;8(4):e60542.
doi: 10.1371/journal.pone.0060542. Print 2013.

The molecular genetic architecture of self-employment

Matthijs J H M van der Loos  1 , 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
Affiliations
Meta-Analysis

The molecular genetic architecture of self-employment

Matthijs J H M van der Loos et al. PLoS One. .

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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Conflict of interest statement

Competing Interests: The authors would like to declare financial support by Philips Medical Systems for the Gutenberg Health Study (GHS). Philips Medical Systems provided the ultrasound machines for the GHS and had no role in the current research. Hence, funding by Philips Medical Systems does not alter the authors' adherence to all the PLOS ONE policies on sharing data and materials.

Figures

Figure 1
Figure 1. Q–Q plots of the self-employment discovery meta-analyses.
Q–Q plot of the self-employment discovery meta-analysis for (A) pooled males and females, (B) males only, and (C) females only. The grey shaded areas in the Q–Q plots represent the 95% confidence bands around the p-values.
Figure 2
Figure 2. Manhattan plots of the self-employment discovery meta-analyses.
Manhattan plot of the self-employment discovery meta-analysis for (A) pooled males and females, (B) males only, and (C) females only. SNPs are plotted on the x-axis according to their position on each chromosome against association with self-employment on the y-axis (shown as −log10 p-value). The solid line indicates the threshold for genome-wide significance (p<5×10−8) and the dashed line the threshold for suggestive SNPs (p<1×10−5).
Figure 3
Figure 3. Prediction results.
Variance explained (Nagelkerke pseudo-R 2 from logistic regression) vs. p-value threshold p T for including SNPs in the score calculation.
See this image and copyright information in PMC

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