The molecular genetic architecture of self-employment.

van der Loos MJHM, Rietveld CA, Eklund N, Koellinger PD, Rivadeneira F, Abecasis GR, Ankra-Badu GA, Baumeister SE, Benjamin DJ, Biffar R, Blankenberg S, Boomsma DI, Cesarini D, Cucca F, de Geus EJC, Dedoussis G, Deloukas P, Dimitriou M, Eiriksdottir G, Eriksson J, Gieger C, Gudnason V, Höhne B, Holle R, Hottenga J, Isaacs A, Järvelin M, Johannesson M, Kaakinen M, Kähönen M, Kanoni S, Laaksonen MA, Lahti J, Launer LJ, Lehtimäki T, Loitfelder M, Magnusson PKE, Naitza S, Oostra BA, Perola M, Petrovic K, Quaye L, Raitakari O, Ripatti S, Scheet P, Schlessinger D, Schmidt CO, Schmidt H, Schmidt R, Senft A, Smith AV, Spector TD, Surakka I, Svento R, Terracciano A, Tikkanen E, van Duijn CM, Viikari J, Völzke H, Wichmann H, Wild PS, Willems SM, Willemsen G, van Rooij FJA, Groenen PJF, Uitterlinden AG, Hofman A, Thurik AR

PLoS ONE 8 (4) e60542 [2013-04-04; online 2013-04-04]

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.

NGI Uppsala (SNP&SEQ Technology Platform) [Service]

National Genomics Infrastructure [Service]

PubMed 23593239

DOI 10.1371/journal.pone.0060542

Crossref 10.1371/journal.pone.0060542

pii: PONE-D-12-39282
pmc: PMC3617140

Publications 9.5.0