Abstract

Creativity is one defining characteristic of human species. There have been mixed findings on how creativity relates to well-being, and little is known about its relationship with career success. We conduct a large-scale genome-wide association study to examine the genetic architecture of occupational creativity, and its genetic correlations with well-being and career success. The SNP-h2 estimates range from 0.08 (for managerial creativity) to 0.22 (for artistic creativity). We record positive genetic correlations between occupational creativity with autism, and positive traits and well-being variables (e.g., physical height, and low levels of neuroticism, BMI, and non-cancer illness). While creativity share positive genetic overlaps with indicators of high career success (i.e., income, occupational status, and job satisfaction), it also has a positive genetic correlation with age at first birth and a negative genetic correlation with number of children, indicating creativity-related genes may reduce reproductive success.

A GWAS study reveals that genes related to occupational creativity are associated with both positive and negative well-being variables, positively correlate with career success, and negatively correlate with reproductive success

Details

Title
A genome-wide association study of occupational creativity and its relations with well-being and career success
Author
Li, Wen-Dong 1   VIAFID ORCID Logo  ; Zhang, Xin 2   VIAFID ORCID Logo  ; Yu, Kaili 1 ; Zhu, Yimo 3 ; Du, Nianyao 4 ; Song, Zhaoli 3 ; Fan, Qiao 5   VIAFID ORCID Logo 

 The Chinese University of Hong Kong, Department of Management, CUHK Business School, Hong Kong, China (GRID:grid.10784.3a) (ISNI:0000 0004 1937 0482) 
 Shanghai University of Finance and Economics, Department of Human Resource Management, School of Business, Shanghai, China (GRID:grid.443531.4) (ISNI:0000 0001 2105 4508) 
 National University of Singapore, Department of Management and Organization, Singapore, Singapore (GRID:grid.4280.e) (ISNI:0000 0001 2180 6431) 
 National University of Singapore, Department of Statistics and Data Science, Singapore, Singapore (GRID:grid.4280.e) (ISNI:0000 0001 2180 6431) 
 National University of Singapore, Centre for Quantitative Medicine, Duke-NUS Medical School, Singapore, Singapore (GRID:grid.4280.e) (ISNI:0000 0001 2180 6431) 
Pages
1092
Publication year
2024
Publication date
2024
Publisher
Nature Publishing Group
e-ISSN
23993642
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
3101006030
Copyright
© The Author(s) 2024. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.