Dataset Information

The molecular genetic architecture of self-employment.

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 (?(g)(2)/?(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.

SUBMITTER: van der Loos MJ

PROVIDER: S-EPMC3617140 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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The molecular genetic architecture of self-employment.

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

PloS one 20130404 4

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 ...[more]

PMID: 23593239

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Project description:We integrated genomic and bioinformatic analyses, using data from the largest genome-wide association study of cocaine dependence (CD; n = 6546; 82.37% with CD; 57.39% male) and the largest postmortem gene-expression sample of individuals with cocaine use disorder (CUD; n = 36; 51.35% with CUD; 100% male). Our genome-wide analyses identified one novel gene (NDUFB9) associated with the genetic predisposition to CD in African-Americans. The genetic architecture of CD was similar across ancestries. Individual genes associated with CD demonstrated modest overlap across European-Americans and African-Americans, but the genetic liability for CD converged on many similar tissue types (brain, heart, blood, liver) across ancestries. In a separate sample, we investigated the neuronal gene expression associated with CUD by using RNA sequencing of dorsal-lateral prefrontal cortex neurons. We identified 133 genes differentially expressed between CUD case patients and cocaine-free control subjects, including previously implicated candidates for cocaine use/addiction (FOSB, ARC, KCNJ9/GIRK3, NR4A2, JUNB, and MECP2). Differential expression analyses significantly correlated across European-Americans and African-Americans. While genes significantly associated with CD via genome-wide methods were not differentially expressed, two of these genes (NDUFB9 and C1qL2) were part of a robust gene coexpression network associated with CUD involved in neurotransmission (GABA, acetylcholine, serotonin, and dopamine) and drug addiction. We then used a "guilt-by-association" approach to unravel the biological relevance of NDUFB9 and C1qL2 in the context of CD. In sum, our study furthers the understanding of the genetic architecture and molecular neuropathology of human cocaine addiction and provides a framework for translating biological meaning into otherwise obscure genome-wide associations.SIGNIFICANCE STATEMENT Our study further clarifies the genetic and neurobiological contributions to cocaine addiction, provides a rapid approach for generating testable hypotheses for specific candidates identified by genome-wide research, and investigates the cross-ancestral biological contributions to cocaine use disorder/dependence for individuals of European-American and African-American ancestries.

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The molecular genetic architecture of self-employment.

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The molecular genetic architecture of self-employment.

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