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Fieder M, Huber S. Genetic Predisposition of Different Social Status Indicators in Men and Women. Twin Res Hum Genet 2024:1-11. [PMID: 39248653 DOI: 10.1017/thg.2024.23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/10/2024]
Abstract
Although there is evidence that social status has a genetic basis, it is less known whether the genetic predisposition differs between men and women as well as among different status indicators and whether there are any intercorrelations among predispositions of status indicators. We therefore investigated the genetic predisposition for different indicators of social status separately for men and women, using polygenic scores obtained from the Wisconsin Longitudinal Study. We used multivariate polygenic regression of 7 different social status indicators on a total of 24 different polygenic scores. We find that in both men and women, wages and education show more associations with polygenic scores than the other status indicators. Also, the genetic predispositions for education and wages are correlated in both men and women, whereas in men more than in women, the genetic predispositions seem to cluster into wages and education on the one hand, and status indicators of position in the hierarchy, on the other hand, with being in a management position somewhere in between. These findings are consistent with an assumption of two different forms of selection pressure associated with either cognitive skill or dominance, which holds true particularly in men. We conclude that the genetic predisposition to higher social status may have changed even though the importance of the cultural trait of social status may have been very constant. Social status may thus be an example of a social trait of constant importance, but with a changing genetic predisposition.
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Affiliation(s)
- Martin Fieder
- Department of Evolutionary Anthropology, University of Vienna, Vienna, Austria
| | - Susanne Huber
- Department of Evolutionary Anthropology, University of Vienna, Vienna, Austria
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Li WD, Zhang X, Yu K, Zhu Y, Du N, Song Z, Fan Q. A genome-wide association study of occupational creativity and its relations with well-being and career success. Commun Biol 2024; 7:1092. [PMID: 39237691 PMCID: PMC11377709 DOI: 10.1038/s42003-024-06686-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2023] [Accepted: 08/06/2024] [Indexed: 09/07/2024] Open
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.
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Affiliation(s)
- Wen-Dong Li
- Department of Management, CUHK Business School, The Chinese University of Hong Kong, Hong Kong, China.
| | - Xin Zhang
- Department of Human Resource Management, School of Business, Shanghai University of Finance and Economics, Shanghai, China.
| | - Kaili Yu
- Department of Management, CUHK Business School, The Chinese University of Hong Kong, Hong Kong, China
| | - Yimo Zhu
- Department of Management and Organization, National University of Singapore, Singapore, Singapore
| | - Nianyao Du
- Department of Statistics and Data Science, National University of Singapore, Singapore, Singapore
| | - Zhaoli Song
- Department of Management and Organization, National University of Singapore, Singapore, Singapore.
| | - Qiao Fan
- Centre for Quantitative Medicine, Duke-NUS Medical School, National University of Singapore, Singapore, Singapore.
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Waszczuk MA, Jonas KG, Bornovalova M, Breen G, Bulik CM, Docherty AR, Eley TC, Hettema JM, Kotov R, Krueger RF, Lencz T, Li JJ, Vassos E, Waldman ID. Dimensional and transdiagnostic phenotypes in psychiatric genome-wide association studies. Mol Psychiatry 2023; 28:4943-4953. [PMID: 37402851 PMCID: PMC10764644 DOI: 10.1038/s41380-023-02142-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Revised: 05/17/2023] [Accepted: 06/16/2023] [Indexed: 07/06/2023]
Abstract
Genome-wide association studies (GWAS) provide biological insights into disease onset and progression and have potential to produce clinically useful biomarkers. A growing body of GWAS focuses on quantitative and transdiagnostic phenotypic targets, such as symptom severity or biological markers, to enhance gene discovery and the translational utility of genetic findings. The current review discusses such phenotypic approaches in GWAS across major psychiatric disorders. We identify themes and recommendations that emerge from the literature to date, including issues of sample size, reliability, convergent validity, sources of phenotypic information, phenotypes based on biological and behavioral markers such as neuroimaging and chronotype, and longitudinal phenotypes. We also discuss insights from multi-trait methods such as genomic structural equation modelling. These provide insight into how hierarchical 'splitting' and 'lumping' approaches can be applied to both diagnostic and dimensional phenotypes to model clinical heterogeneity and comorbidity. Overall, dimensional and transdiagnostic phenotypes have enhanced gene discovery in many psychiatric conditions and promises to yield fruitful GWAS targets in the years to come.
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Affiliation(s)
- Monika A Waszczuk
- Department of Psychology, Rosalind Franklin University of Medicine and Science, North Chicago, IL, USA.
| | - Katherine G Jonas
- Department of Psychiatry, Stony Brook University School of Medicine, Stony Brook, NY, USA
| | | | - Gerome Breen
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- UK National Institute for Health and Care Research (NIHR) Biomedical Research Centre, South London and Maudsley NHS Trust, London, UK
| | - Cynthia M Bulik
- Department of Psychiatry, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Anna R Docherty
- Huntsman Mental Health Institute, Department of Psychiatry, University of Utah School of Medicine, Salt Lake City, UT, USA
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University School of Medicine, Richmond, VA, USA
| | - Thalia C Eley
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- UK National Institute for Health and Care Research (NIHR) Biomedical Research Centre, South London and Maudsley NHS Trust, London, UK
| | - John M Hettema
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University School of Medicine, Richmond, VA, USA
- Department of Psychiatry, Texas A&M Health Sciences Center, Bryan, TX, USA
| | - Roman Kotov
- Department of Psychiatry, Stony Brook University School of Medicine, Stony Brook, NY, USA
| | - Robert F Krueger
- Psychology Department, University of Minnesota, Minneapolis, MN, USA
| | - Todd Lencz
- Department of Psychiatry, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
- Department of Psychiatry, Division of Research, The Zucker Hillside Hospital Division of Northwell Health, Glen Oaks, NY, USA
- Institute for Behavioral Science, The Feinstein Institutes for Medical Research, Manhasset, NY, USA
| | - James J Li
- Department of Psychology, University of Wisconsin, Madison, WI, USA
- Waisman Center, University of Wisconsin, Madison, WI, USA
| | - Evangelos Vassos
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- UK National Institute for Health and Care Research (NIHR) Biomedical Research Centre, South London and Maudsley NHS Trust, London, UK
| | - Irwin D Waldman
- Department of Psychology, Emory University, Atlanta, GA, USA
- Center for Computational and Quantitative Genetics, Emory University, Atlanta, GA, USA
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Zhu C, Zhao Q, He J, Böckerman P, Luo S, Chen Q. Genetic basis of STEM occupational choice and regional economic performance: a UK biobank genome-wide association study. Hum Genomics 2023; 17:40. [PMID: 37165452 PMCID: PMC10170832 DOI: 10.1186/s40246-023-00488-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Accepted: 05/06/2023] [Indexed: 05/12/2023] Open
Abstract
BACKGROUND Science, technology, engineering, and mathematics (STEM) professionals are regarded as the highly skilled labor force that fosters economic productivity, enterprise innovation, and international competitiveness of a country. This study aims to understand the genetic predisposition to STEM occupations and investigate its associations with regional economic performance. We conducted a genome-wide association study on the occupational choice of STEM jobs based on a sample of 178,976 participants from the UK Biobank database. RESULTS We identified two genetic loci significantly associated with participants' STEM job choices: rs10048736 on chromosome 2 and rs12903858 on chromosome 15. The SNP heritability of STEM occupations was estimated to be 4.2%. We also found phenotypic and genetic evidence of assortative mating in STEM occupations. At the local authority level, we found that the average polygenic score of STEM is significantly and robustly associated with several metrics of regional economic performance. CONCLUSIONS The current study expands our knowledge of the genetic basis of occupational choice and potential regional disparities in socioeconomic developments.
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Affiliation(s)
- Chen Zhu
- College of Economics and Management, China Agricultural University, No. 17 Qinghuadonglu, Haidian Dist., Beijing, China.
| | - Qiran Zhao
- College of Economics and Management, China Agricultural University, No. 17 Qinghuadonglu, Haidian Dist., Beijing, China
| | - Jianbo He
- College of Agriculture, Nanjing Agricultural University, Nanjing, China
| | - Petri Böckerman
- School of Business and Economics, University of Jyväskylä, Jyvaskyla, Finland
| | - Siyang Luo
- Department of Psychology, Sun Yat-Sen University, Guangzhou, China
| | - Qihui Chen
- College of Economics and Management, China Agricultural University, No. 17 Qinghuadonglu, Haidian Dist., Beijing, China.
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Qiu S, Hu Y, Zou Q, Liu G. Genetic variant rs9848497 up-regulates MST1R expression, thereby influencing leadership phenotypes. Proc Natl Acad Sci U S A 2022; 119:e2207847119. [PMID: 35787185 PMCID: PMC9303931 DOI: 10.1073/pnas.2207847119] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Affiliation(s)
- Shizheng Qiu
- School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China
| | - Yang Hu
- School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China
| | - Quan Zou
- Yangtze Delta Region Institute (Quzhou), University of Electronic Science and Technology of China, Quzhou 313001, China
- Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Guiyou Liu
- Beijing Institute of Brain Disorders, Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing 100069, China
- Chinese Institute for Brain Research, Beijing 102206, China
- Key Laboratory of Cerebral Microcirculation in Universities of Shandong, Department of Neurology, Second Affiliated Hospital, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian 271000, China
- Beijing Key Laboratory of Hypoxia Translational Medicine, National Engineering Laboratory of Internet Medical Diagnosis and Treatment Technology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
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