The Molecular Genetic Architecture of Self-Employment
File(s)
Author(s)
Type
Journal Article
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 (σg2/σP2 = 25%, h2 = 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.
Date Issued
2013-04-04
Date Acceptance
2013-02-27
Citation
PLOS One, 2013, 8 (4)
ISSN
1932-6203
Publisher
Public Library of Science
Journal / Book Title
PLOS One
Volume
8
Issue
4
Copyright Statement
© 2013 van der Loos et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Identifier
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000319108100052&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
Subjects
Science & Technology
Multidisciplinary Sciences
Science & Technology - Other Topics
MULTIDISCIPLINARY SCIENCES
GENOME-WIDE ASSOCIATION
CORONARY HEART-DISEASE
COMMON SNPS EXPLAIN
CARDIOVASCULAR-DISEASE
SOCIOECONOMIC-STATUS
EDUCATIONAL-ATTAINMENT
MISSING HERITABILITY
LARGE PROPORTION
RISK-FACTORS
HUMAN HEIGHT
Employment
Female
Gene-Environment Interaction
Genome-Wide Association Study
Genotype
Humans
Intelligence
Male
Models, Theoretical
Multifactorial Inheritance
Personality
Polymorphism, Single Nucleotide
Registries
Twins, Dizygotic
Twins, Monozygotic
General Science & Technology
MD Multidisciplinary
Publication Status
Published
Article Number
ARTN e60542